{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b25da1cb",
   "metadata": {},
   "source": [
    "## 题目一：请筛选出拥有地铁站点最多的前15的城市制作成柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "94485ccc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>站点名称</th>\n",
       "      <th>POI编号</th>\n",
       "      <th>拼音名称</th>\n",
       "      <th>gd经度</th>\n",
       "      <th>gd纬度</th>\n",
       "      <th>路线名称</th>\n",
       "      <th>城市名称</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>金安桥</td>\n",
       "      <td>BV11494889</td>\n",
       "      <td>JinAn Qiao</td>\n",
       "      <td>116.162586</td>\n",
       "      <td>39.923298</td>\n",
       "      <td>S1线</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>四道桥</td>\n",
       "      <td>BV10813547</td>\n",
       "      <td>si dao qiao</td>\n",
       "      <td>116.134010</td>\n",
       "      <td>39.916030</td>\n",
       "      <td>S1线</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>桥户营</td>\n",
       "      <td>BV10813541</td>\n",
       "      <td>qiao hu ying</td>\n",
       "      <td>116.125809</td>\n",
       "      <td>39.912383</td>\n",
       "      <td>S1线</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>上岸</td>\n",
       "      <td>BV10813543</td>\n",
       "      <td>shang an</td>\n",
       "      <td>116.122225</td>\n",
       "      <td>39.905138</td>\n",
       "      <td>S1线</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>栗园庄</td>\n",
       "      <td>BV10813544</td>\n",
       "      <td>li yuan zhuang</td>\n",
       "      <td>116.123254</td>\n",
       "      <td>39.895780</td>\n",
       "      <td>S1线</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5029</th>\n",
       "      <td>锡林公园</td>\n",
       "      <td>BV10875474</td>\n",
       "      <td>XiLin GongYuan</td>\n",
       "      <td>111.687460</td>\n",
       "      <td>40.770883</td>\n",
       "      <td>2号线</td>\n",
       "      <td>呼和浩特</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5030</th>\n",
       "      <td>内大南校区</td>\n",
       "      <td>BV10875440</td>\n",
       "      <td>NeiDaNan XiaoQu</td>\n",
       "      <td>111.692463</td>\n",
       "      <td>40.759146</td>\n",
       "      <td>2号线</td>\n",
       "      <td>呼和浩特</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5031</th>\n",
       "      <td>帅家营</td>\n",
       "      <td>BV10875453</td>\n",
       "      <td>ShuaiJiaYing</td>\n",
       "      <td>111.706981</td>\n",
       "      <td>40.755604</td>\n",
       "      <td>2号线</td>\n",
       "      <td>呼和浩特</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5032</th>\n",
       "      <td>喇嘛营</td>\n",
       "      <td>BV10875441</td>\n",
       "      <td>LaMaYing</td>\n",
       "      <td>111.731336</td>\n",
       "      <td>40.755684</td>\n",
       "      <td>2号线</td>\n",
       "      <td>呼和浩特</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5033</th>\n",
       "      <td>阿尔山路</td>\n",
       "      <td>BV10875438</td>\n",
       "      <td>AErShan Lu</td>\n",
       "      <td>111.747816</td>\n",
       "      <td>40.755465</td>\n",
       "      <td>2号线</td>\n",
       "      <td>呼和浩特</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5034 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       站点名称       POI编号             拼音名称        gd经度       gd纬度 路线名称  城市名称\n",
       "0       金安桥  BV11494889       JinAn Qiao  116.162586  39.923298  S1线    北京\n",
       "1       四道桥  BV10813547      si dao qiao  116.134010  39.916030  S1线    北京\n",
       "2       桥户营  BV10813541     qiao hu ying  116.125809  39.912383  S1线    北京\n",
       "3        上岸  BV10813543         shang an  116.122225  39.905138  S1线    北京\n",
       "4       栗园庄  BV10813544   li yuan zhuang  116.123254  39.895780  S1线    北京\n",
       "...     ...         ...              ...         ...        ...  ...   ...\n",
       "5029   锡林公园  BV10875474   XiLin GongYuan  111.687460  40.770883  2号线  呼和浩特\n",
       "5030  内大南校区  BV10875440  NeiDaNan XiaoQu  111.692463  40.759146  2号线  呼和浩特\n",
       "5031    帅家营  BV10875453     ShuaiJiaYing  111.706981  40.755604  2号线  呼和浩特\n",
       "5032    喇嘛营  BV10875441         LaMaYing  111.731336  40.755684  2号线  呼和浩特\n",
       "5033   阿尔山路  BV10875438       AErShan Lu  111.747816  40.755465  2号线  呼和浩特\n",
       "\n",
       "[5034 rows x 7 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "df=pd.read_csv('metro.csv',encoding='gbk',sep=',')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "42f56e0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "上海      535\n",
       "北京      413\n",
       "成都      356\n",
       "广州      284\n",
       "深圳      284\n",
       "武汉      243\n",
       "杭州      225\n",
       "重庆      218\n",
       "南京      174\n",
       "西安      166\n",
       "天津      159\n",
       "郑州      146\n",
       "苏州      135\n",
       "香港      131\n",
       "长沙      114\n",
       "青岛      111\n",
       "昆明      106\n",
       "宁波      103\n",
       "合肥      100\n",
       "大连       93\n",
       "长春       92\n",
       "沈阳       92\n",
       "南宁       87\n",
       "南昌       74\n",
       "无锡       69\n",
       "石家庄      63\n",
       "贵阳       57\n",
       "厦门       54\n",
       "福州       47\n",
       "呼和浩特     44\n",
       "济南       42\n",
       "徐州       38\n",
       "常州       29\n",
       "哈尔滨      28\n",
       "佛山       25\n",
       "太原       23\n",
       "乌鲁木齐     21\n",
       "兰州       20\n",
       "温州       18\n",
       "东莞       15\n",
       "Name: 城市名称, dtype: int64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_city_metro_num = df['城市名称'].value_counts()\n",
    "df_city_metro_num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c711815b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'city': Index(['上海', '北京', '成都', '广州', '深圳', '武汉', '杭州', '重庆', '南京', '西安', '天津', '郑州',\n",
       "        '苏州', '香港', '长沙'],\n",
       "       dtype='object'),\n",
       " 'num': array([535, 413, 356, 284, 284, 243, 225, 218, 174, 166, 159, 146, 135,\n",
       "        131, 114], dtype=int64)}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_city_metro_num = df['城市名称'].value_counts()\n",
    "dict_city_metro_num = {'city':df_city_metro_num.index[0:15],'num':df_city_metro_num.values[0:15]}\n",
    "dict_city_metro_num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cb70d65f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>上海</td>\n",
       "      <td>535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>北京</td>\n",
       "      <td>413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>成都</td>\n",
       "      <td>356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>广州</td>\n",
       "      <td>284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>深圳</td>\n",
       "      <td>284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>武汉</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>杭州</td>\n",
       "      <td>225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>重庆</td>\n",
       "      <td>218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>南京</td>\n",
       "      <td>174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>西安</td>\n",
       "      <td>166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>天津</td>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>郑州</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>苏州</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>香港</td>\n",
       "      <td>131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>长沙</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   city  num\n",
       "0    上海  535\n",
       "1    北京  413\n",
       "2    成都  356\n",
       "3    广州  284\n",
       "4    深圳  284\n",
       "5    武汉  243\n",
       "6    杭州  225\n",
       "7    重庆  218\n",
       "8    南京  174\n",
       "9    西安  166\n",
       "10   天津  159\n",
       "11   郑州  146\n",
       "12   苏州  135\n",
       "13   香港  131\n",
       "14   长沙  114"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_city_metro_num = df['城市名称'].value_counts()\n",
    "dict_city_metro_num = {'city':df_city_metro_num.index[0:15],'num':df_city_metro_num.values[0:15]}\n",
    "df_city_15 = pd.DataFrame(dict_city_metro_num)\n",
    "df_city_15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "27797926",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 4000x1600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,8),dpi=200)\n",
    "x_label=df_city_metro_num.index[0:15]\n",
    "y_label=df_city_metro_num.values[0:15]\n",
    "plt.bar(x_label,y_label,color='orange')\n",
    "for x,y in zip(x_label,y_label):\n",
    "    plt.text(x,y,'%.2f'%y,ha='center',va='bottom')\n",
    "plt.rcParams['font.sans-serif']=['simhei'] # 显示中文\n",
    "plt.rcParams['axes.unicode_minus']=False # 显示中文\n",
    "plt.xlabel(\"城市\")\n",
    "plt.ylabel(\"地铁站数量\")\n",
    "plt.title(\"全国地铁站点数量排名前15的城市\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ffac5fd",
   "metadata": {},
   "source": [
    "## 题目二：请筛选出拥有地铁线路最多的前15的城市制作成柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "53e44166",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('北京', 24),\n",
       " ('上海', 19),\n",
       " ('广州', 16),\n",
       " ('成都', 12),\n",
       " ('香港', 11),\n",
       " ('南京', 10),\n",
       " ('武汉', 10),\n",
       " ('深圳', 10),\n",
       " ('重庆', 10),\n",
       " ('西安', 8),\n",
       " ('大连', 7),\n",
       " ('杭州', 7),\n",
       " ('郑州', 7),\n",
       " ('天津', 6),\n",
       " ('昆明', 6),\n",
       " ('长沙', 6),\n",
       " ('青岛', 6),\n",
       " ('苏州', 5),\n",
       " ('长春', 5),\n",
       " ('南宁', 4),\n",
       " ('合肥', 4),\n",
       " ('宁波', 4),\n",
       " ('沈阳', 4),\n",
       " ('南昌', 3),\n",
       " ('无锡', 3),\n",
       " ('济南', 3),\n",
       " ('石家庄', 3),\n",
       " ('厦门', 2),\n",
       " ('呼和浩特', 2),\n",
       " ('哈尔滨', 2),\n",
       " ('徐州', 2),\n",
       " ('福州', 2),\n",
       " ('贵阳', 2),\n",
       " ('东莞', 1),\n",
       " ('乌鲁木齐', 1),\n",
       " ('佛山', 1),\n",
       " ('兰州', 1),\n",
       " ('太原', 1),\n",
       " ('常州', 1),\n",
       " ('温州', 1)]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_Line=df.groupby(\"城市名称\")['路线名称'].value_counts() #统计同城地铁站的数量，并按降序的形式排序\n",
    "# 统计单个城市拥有地铁线路的数量\n",
    "dict_city_line={}\n",
    "for i in range(len(city_Line)):\n",
    "    dict_city_line[city_Line.index[i][0]]=dict_city_line.get(city_Line.index[i][0],0) + 1\n",
    "dict_sort=sorted(dict_city_line.items(), key=lambda x: x[1],reverse=True)#用了一个匿名函数用于排序值\n",
    "dict_sort"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6014e478",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['北京',\n",
       " '上海',\n",
       " '广州',\n",
       " '成都',\n",
       " '香港',\n",
       " '南京',\n",
       " '武汉',\n",
       " '深圳',\n",
       " '重庆',\n",
       " '西安',\n",
       " '大连',\n",
       " '杭州',\n",
       " '郑州',\n",
       " '天津',\n",
       " '昆明']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cities = [dict_sort[i][0]for i in range(15)]\n",
    "num=[dict_sort[i][1]for i in range(15)]\n",
    "cities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "771df35f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure() #创建空图\n",
    "plt.figure(figsize=(20,8), dpi=100)# 画布大小设置\n",
    "x_label = cities #x铀的坐标\n",
    "y_label = num # y轴的值\n",
    "plt.bar(x_label,y_label,color='pink')  #构建柱状阁\n",
    "for x,y in zip(x_label,y_label):  #在桂子上添加数值\n",
    "    plt.text(x,y,'%.2f'%y,ha=\"center\",va='bottom')\n",
    "plt.rcParams[\"font.sans-serif\"]=['simhei']#显示中文\n",
    "plt.rcParams['axes.unicode_minus']=False#显示中文\n",
    "plt.title(\"地铁线路最多的前15的城市\",fontsize=28)#设置标您,这里只结显示英文,中文显示乱码\n",
    "plt.ylabel(\"数量\")#i设置糖名称\n",
    "plt.xlabel(\"城市\")#没置x拙名称\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44908d1d",
   "metadata": {},
   "source": [
    "## 题目三:统计广州换乘次数为1次、2次、大于等于3次的站点个数（例如广州的嘉禾望岗可换乘2号线、3号线、14号线，则计为可换乘次数为2次），并以饼状图的形式展示换乘站点的比例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "39f34b97",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "城市名称  路线名称        \n",
       "广州    6号线             31\n",
       "      8号线             26\n",
       "      广佛线             25\n",
       "      2号线             24\n",
       "      5号线             24\n",
       "      4号线             23\n",
       "      21号线            21\n",
       "      1号线             16\n",
       "      3号线             16\n",
       "      3号线(北延段)        15\n",
       "      14号线            13\n",
       "      13号线            11\n",
       "      9号线             11\n",
       "      14号线支线(知识城线)    10\n",
       "      7号线              9\n",
       "      APM线             9\n",
       "Name: 路线名称, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_广州=df.query(\"城市名称=='广州'\")\n",
    "city_station=df_广州.groupby(\"城市名称\")[\"路线名称\"].value_counts()\n",
    "city_station"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "39821e19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city</th>\n",
       "      <th>station</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>广州</td>\n",
       "      <td>6号线</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>广州</td>\n",
       "      <td>8号线</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>广州</td>\n",
       "      <td>广佛线</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>广州</td>\n",
       "      <td>2号线</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>广州</td>\n",
       "      <td>5号线</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>广州</td>\n",
       "      <td>4号线</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>广州</td>\n",
       "      <td>21号线</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>广州</td>\n",
       "      <td>1号线</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>广州</td>\n",
       "      <td>3号线</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>广州</td>\n",
       "      <td>3号线(北延段)</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>广州</td>\n",
       "      <td>14号线</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>广州</td>\n",
       "      <td>13号线</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>广州</td>\n",
       "      <td>9号线</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>广州</td>\n",
       "      <td>14号线支线(知识城线)</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>广州</td>\n",
       "      <td>7号线</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>广州</td>\n",
       "      <td>APM线</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   city       station  num\n",
       "0    广州           6号线   31\n",
       "1    广州           8号线   26\n",
       "2    广州           广佛线   25\n",
       "3    广州           2号线   24\n",
       "4    广州           5号线   24\n",
       "5    广州           4号线   23\n",
       "6    广州          21号线   21\n",
       "7    广州           1号线   16\n",
       "8    广州           3号线   16\n",
       "9    广州      3号线(北延段)   15\n",
       "10   广州          14号线   13\n",
       "11   广州          13号线   11\n",
       "12   广州           9号线   11\n",
       "13   广州  14号线支线(知识城线)   10\n",
       "14   广州           7号线    9\n",
       "15   广州          APM线    9"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_city_station = {'city':[i[0]for i in city_station.index],'station':[i[1]for i in city_station.index],'num':city_station.values}\n",
    "df_city_station = pd.DataFrame(dict_city_station)\n",
    "df_city_station"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "fc2548d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "station_count2 = len(df_city_station.query('num==2'))\n",
    "station_count3 = len(df_city_station.query('num==3'))\n",
    "station_count4 = len(df_city_station.query('num>=4'))\n",
    "fig = plt.figure() #创建空图\n",
    "plt.figure(figsize=(20,8), dpi=100)# 画布大小设置\n",
    "x_label = [station_count2,station_count3,station_count4]\n",
    "y_label = [\"单个站点换乘1\",\"单个站点换乘2\",\"单个站点换乘3\"]\n",
    "plt.pie(x_label,labels=y_label,autopct='%1.1f%%')  \n",
    "plt.rcParams[\"font.sans-serif\"]=['simhei'] #显示中文\n",
    "plt.rcParams['axes.unicode_minus']=False #显示中文\n",
    "plt.title(\"广州单站点换成次数的比例发布\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b0cbaaf",
   "metadata": {},
   "source": [
    "## 题目四：统计同一城市中换乘站点最多的前15的城市，并以折线图展示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b611b9c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>北京</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>上海</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>广州</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>成都</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>香港</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>南京</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>重庆</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>深圳</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>武汉</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>西安</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>杭州</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>郑州</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>大连</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>青岛</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>长沙</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   city  num\n",
       "0    北京   24\n",
       "1    上海   19\n",
       "2    广州   16\n",
       "3    成都   12\n",
       "4    香港   11\n",
       "5    南京   10\n",
       "6    重庆   10\n",
       "7    深圳   10\n",
       "8    武汉   10\n",
       "9    西安    8\n",
       "10   杭州    7\n",
       "11   郑州    7\n",
       "12   大连    7\n",
       "13   青岛    6\n",
       "14   长沙    6"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_station=df.groupby(\"城市名称\")[\"路线名称\"].value_counts()\n",
    "dict_city_station = {'city':[i[0]for i in city_station.index],'station':[i[1]for i in city_station.index],'num':city_station.values}\n",
    "df_city_station = pd.DataFrame(dict_city_station)\n",
    "df_tran_station_city = df_city_station.query('num>=2')['city'].value_counts()\n",
    "dict_tran_station_city = {'city' : df_tran_station_city.index[0:15],'num':df_tran_station_city.values[0:15]}\n",
    "df_tran_station_city_10 = pd.DataFrame(dict_tran_station_city)\n",
    "df_tran_station_city_10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0590e28c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure() #创建空图\n",
    "plt.figure(figsize=(20,8), dpi=100)# 画布大小设置\n",
    "x_label = df_tran_station_city.index[0:15] #x铀的坐标\n",
    "y_label = df_tran_station_city.values[0:15] # y轴的值\n",
    "plt.plot(x_label,y_label,color='orange')  #构建柱状阁\n",
    "for x,y in zip(x_label,y_label):  #在桂子上添加数值\n",
    "    plt.text(x,y,'%.2f'%y,ha=\"center\",va='bottom')\n",
    "plt.rcParams[\"font.sans-serif\"]=['simhei']#显示中文\n",
    "plt.rcParams['axes.unicode_minus']=False#显示中文\n",
    "plt.title(\"地铁换乘次数排名前15的城市\",fontsize=28)#设置标您,这里只结显示英文,中文显示乱码\n",
    "plt.ylabel(\"数量\")#i设置糖名称\n",
    "plt.xlabel(\"城市\")#没置x拙名称\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42afc371",
   "metadata": {},
   "source": [
    "## 题目五:统计广州地铁线路各线路站点的数量，并以横向柱转图展示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1c9c367c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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erl/jIeA/6vuqVZ4bQdCNmfmxav/KwDbAsRHxVnqHKw1zKdWQdwInVfseqQeig+jb3dWq2O8B/nsQp06iDDXfAPhumzaN1asHXdWWmQsj4hTK4km9DlGefxRVwAh8NjNvqc67OyIupgTNV1HCvrkRMZWeUHTAq2pHxPOBjTPz1236+UeaFiaKiJcBv682D8rMswdyryrUfTulQnZ7ev4sTa9PGzDAfq9ECVbfCmwSEZPafD7eQ1ksa15EnJqZxw3mPsPksSV8/QF//qppMo6iTCPRCDOPz8xjm1aPHwXsC1xDmabhwxGxoJq6oNefdWBTytD4ZmvV3jcvrtWfUZRAfrChvCRJS92y8I8DSZKkJaUetoxs22rpaQzFfZQ2i+RUAdT3KUHgehHx0sy8oc31TqzarUxZMGhQoeggHQR8tc2xXwFfAX6UmU82hTRDlpk3RcR5lPkzH6EsKtMY/vsRSvg5pno9U53zXeC71aJBV7a59Pjq61DmYYUyJP+/gfOB31AC7nson7FbKaHoHcCnmp6nVRVofWj8+BbHgecWNno5ZW7P3YGXAbfROpxeEt5MCdnqjouIhwcarlaeBo6hZz7Wl1O+h83+rfo6jqZqxKWoPi/x1zKzvykI+hURBwJnVZsDquyOiNcAn6VnSoangSMyszH9Rj1MH5OZD0fEXsDvKAHnJyPiahat6t2C1ibV3vcVet9PWUhpYbvXcFf5VtOGNBaQWolSMboKZZ5iSZIGxVBUkiStyJaZUDQi1qUn9Lq9eQGUJhfQUx35Zsr8kovIzAcj4tuUwPIlEbF7Zv5smLrc7EzgE8ALKMPO/0lP5ev/y8wrlsRNM/M3VKFZRGxVO/Tb6li7837Yx2XHVV+fHGKf/h4RG7VYxOYoSoUqwHsHuPjV3ylVpgFMqkKfKZQV6BuvzYEX01T5Cbw4Ikb1txjX4oiIf6eEu2+udiVluPYelO/jWRHxX5Sq0X4XOMrMjIiLKEPyAfamdSjaGB7+DPCToT/BYlli39dKv5Wi1aJeb6MnEP0XsG9m/rLWrL4a+6oAmXlXRLwFuAR4N7Abvae8gLLQVyuTq69/z8zmBeueU019cEd/zzCcqpD1Wcr37gnKL0skSRoSQ1FJkrQiizbvO2Hz2vtb+mn7a8pcfmtThhl/vI+2n6OEolCqRZdIKFoNGz+RUsH3ReBA4H+XxL0WR0SMpu/5Y8fUjj8VEau3aNNYwGk1YI3GokN1LQLRyZTQGODszGw3F2z9nBdSgqknKNVuz6NUjjaHV83uBWYCf6Is7LRIeFdVlo6vNh/KzEf760/T+a+gBJdvpcxPCTALODAzr6zmtvwWsCGwA/DziLgROBv4Tmb2tdjQ9+kJRfeiaRX1KJPONipFf5eZ/xpM34fRcM+H2azfULRaPOiQiJhLCcjfk5nPDWmPiPdQPi8HUCpb762d++uI2LC6T2NO3meAy4A9KQukrdbis7Fe9bXdvMdtRcS/Aa3m8R1OV2Tmzv03kySpb4aikiRpRVb/u05flZlLw8tr7//Ups2zUKqhIuISStCxcUS0G+ZKZt4SEVcCrwJ2j4iXDFeHW9zr8433/S2W1I8luXDONxn4YjebMrBKsz4ftgrxzqBU6T1ECaeb26wGHEeprp1CGYq+ZovL1QPRhZTV6P8I3EzPavQDGSp8GPA/1fs3AD/u5xlGAttSwrJ30FPxCmW6h88CJ2XmYwCZeW1EbE6Z5/KjlGffqnqdEhHXAxe2WV39GnpC/00jYnJmzqodX48S9kJtobGIOID+p4j4eR+fzd9l5vb9nF+3pEPRwSyM9rE2Q9GPoXyeHqUMqb+gfrCqJp9BTzXpDyiLp+1J+e/jdvT+Hr+g1nbQoSjwcNN2f9XYjZ9zo/qznRH0/DLD6lBJ0rAY0X8TSZKk5VZ9yPySDjj60y4UrS9IUh+q+tPa+3f0c+36XJ+LBHLLoHq403aIckQ8LyLWiYjVIqL5l/kREStFxCoRMSEiJkXEuJYXWvKOAF5TvT+8TWXjY8D7gf0plZWtAlEoixm9izLf42qZuXlm7g98iTJlwEDnTpxbez+vxfH3RsQPIuJnEfEbyqJGV1CqkhuB6OPA54ENM/P/NQLRhsx8PDP/H2Wu3NPpCflGUBbluqdVx6pw7+LaruYV3uvB/tW194s7nH2wYdqSri4f8C8HWgWi1SJdU6rNxiJnrZxJmfP3CUp1d/17umtT23po3O6XN331s/7fsH9k5ph2L3ov6PTjftruWWs71LmAJUnqxUpRSZK0Ilu19n4wVVnDqqok3La264+19xNq7+uh0+WU6tY7aR1q1f2QMux6VXov3LOsWrv2vq+fy8n0LKzUrNWq6++jLHR0CSU4eZISpD1DCaCSEk7XFwy6lZ6FbxpWomf4/Fj6EBGvo1RRAlxSLfS0iGouzTuAzSg//+uA66v3q9JTrTcrM89tcYnPATtFxFsz87a++lSph1OtqvW2a9p+L6WS9XhKtd/XgJMz85/93Sgz76MM8f408GHKdA6XZuZ5fZz2E8oUDFDmJ/1K7VgjFE3KIlsN9c/KZcCl/fWN8ueu8UuFQU0hwJKfh3hA14+IN1B+Pk81vTauNfsncGIfVbLXAZ9ohOoRcR9lsas9gWNr7eqhaLsF3vrzNEv235n9TjsgSdJAGIpKkqQVUkSMoazK3tB2wZClYFN6Fvd5qD4nIL1D0ef2Z+ZDEbFNZl4PUM3h2FJmPhER+wM3ZOb9w7X6+5IQEZOAN9Z2zRrO61eVi33dvzlMXZ8yB2hfc2C2us5I4FBKIDqKEri9r9o/gRL8Pq96rVqt0P6fwB2ZOb/pWqtSQtsR9J57tnH8rZRQDOD6iDgG+GJm9lX9XK+qbNXur8ACSvC7atX+FEo15eOUOSg/OshpEmZl5voR8Qn6ntcVSgjceOadmxaM2qz6+ufMfLh2zoLa+2sz89T+OlSt9t4IRQf7i5FlIhQFXsSi1bTNXkr7hZMAZjZVGV8C/BewZURskJl/rfY3/jvzNGW6hqFoTFXy/IgY6LQlbxxE205PhSJJWkEYikqSpBXV+KbtTs5DN4cyJHoSvatXATaqvb+3fqARiA5EZvY5Z2QnVfOcHkEZEr4VPVM4zQNu6uPUS4G/UcKwhZShvq+tjp1G+X6NpCxStCr9DPetFlVqrpBchTKsvc8wtYU/UsLuhhGUys8JLDrs+lJK8Nry55mZj0XErZQwcLOIWKUxDDkitgPOaervK4ELgPsH2ee6T1VBbbMvVtWvQ7EAIDP7q2wmM+dGxM2Uz8MalOH2v60Ob1N9vbbptMWtgh7sXLb1X6q8MiK+uJj3B9ikzfX7kpTK50cpgfWTlArmRsX1P+k9XULDiymfy2TROWUvoISiAP8BfDIi1qFnmo9rBrs4F0BE1Of+hCUzp2inF82TJK0gDEUlSdKK6kVN251awZrM/DvQakg09ARrczLzoaXUpaXtbkp16MSm/Z9snqeyrnkYebVYUSMUPT8zfzPIfrydniDqbmBdSijzwYg4LTNbBUvt/Jreoegq1auVgQx3v5ISiq5CWRjpexGxLWWYeOO6/wLemZmXDaKfQ1Gvqv4uZeh1Xz5HCa0GO9fjVZRQFGAn4LcRMZGyoj3A75raL8kFulqpL3o1tXoNp3afl14y80uUOWWfExE/A3ajVHS+IjPvbDo+FZhZbV6Zmc3zu/4SaAyhPzgijgfeSU/16lA/Y/Vn+kdmrtOuYfVLisYvq36cmfv00fY1wM+rTf8NK0kaFv4PRZIkragm194/lJnL3OIcETGBnn4OdajqUhMRrwIiM6/op2m9UmxUZi6IiNMpK2VDmavwY0sh3Gt2cO3914CXAW+lVBUfA3xkENf6GT1D2udSVuq+i1LZ+kD1+jswm9q0CH34KfDf1ft3RcSjlECysRL4fcAumXnHIPo4VPWh9z9rU1H6nIg4qXo72Lker6d8v35JT5XoK2rHmytFl7bmqu5l4vrVVBq7VZtnNgeilQ/U3n+t+WBmPhMRXwU+BTyfMhVEfUG3dos29aceij4/Iga6ONYb+mlbrw4d3baVJEmDYCgqSZJWVPW5GWd1qhP92IOeoeTXdLIj7UTEesDbKIvnbAocQlmlvC/1YcGNv2+eTXnWCzLzD8PbS4iIsQDN83XWju9Nz2JXT1T9+Q0lFAU4PCLOycyZLU5v5arq3N9VCw0trl9SFjgaT/lcvI6ez8YsSiB69zDcZyCGusr7YM/7dmae07Rvx+rrYwxh9fPhlJm79d+qIz5VfX2CFtM+RMQL6VnE6m7g+22uczrwCUrI+P+AMdX+q2pzjA7WmKbtgc6bGoNo2+fiZ5IkDdSI/ptIkiQtl15ee39Lx3rRt71q73/RsV70Vq/IehslkDuRnqHiA5mbdfXa+1UAMvMvmXn0EgpE1wZ+Ral2a3V8NPCZ2q6vZ+Y/MvNqelZ9Xxn4RkQMqGggM2dn5oXDFIiSmU/SM8XCSHr+nv5nYMelEYhGxL9Xb4c6TH1Q57VZKGqX6usfgGcjYmpEHBwRLX+2S0JErBMRr1xa9xuMiHg9ZW5dKJ/ZH0bESRHxhqryHOBkesLJ/223IFc1Xcc3q816mPn5ofYvM+/LzBjIizKXbMP/DfS8zNyl3f0lSRoMQ1FJkrTCiYhxwA61XTd0qi/tRMTzgDdXmw/RM3y4E31ZPyIOreYprAci9eG9jwMXUsKq/tTnYhzXx31fHBFnRMS/DarDva+xPqXi86XAh6qAtNn/AI3Abz5wfO3Yh+kJ87alrCa/2CJiVERsGRGHRMTZEfHniNigj/Zj6ZlLs+GvlEB0WILXNvcdX/Xxt8DV1e6lPXcnETGiGhbemGN0KmVagpmU4d/vaHfuEvBu4KrqZ/aVRhVyXUS8JSLaVjZGxP4R8cm+bhIR0yLixxExmIWD1qFUlT9N+bfcy4APAf8HzI6Iv1B+mQFwMz2hZzufBeqh6S3ARYPoz3MiYqWIeF5ELLFpB6p7TKj+Gy9J0mJx+LwkSVoRvZXelU9XdKgffXk/PXPjnZeZQx2yPGQR8VrgC8BGbZo8BlxCWan6J5m5oE27Xn+nzMwzgTMH0IWXA+8BDoyIa4FpmTngFdWr/n+HsuI7lKHnr6cMjW+0eRNwVO20j2Xmc3N8ZuaNEXEacHi164MR8afMPGuAfQjg34ANKCuLb04JaLdk0TkjW85rGxEvoQxx3rjp0LqUocIPNbUfBWyWmTcNpI9tvC4i3kxZuKox3cHDjVssxnX7VQXXm1SvzYAtKGFoPXxsXpSreXtJOqD6uhHwr/qUDBHxFuCjwDaU/85cWD+xWjzoUsrcqE9HxPmZeXtTm5Upq8HvXu36T+DrA+lYZn6DUtG8BmVxql2AnSnfwxGUFecbXly1/XJm/r7NJbend6HMWpRwfihz106lmhu5ynmfpnfg2pe9I6KveZ9HVq/GZ/NzlF9oSJI0ZIaikiRphRIRIyiVUw33ZGZH5yZsFhHPB46s7RpIIFKvShuu0Op39ASKDU9RFv35NvDTPlaHz9r7Fwzx/o05G0dRhuf/YxDnfhDYh55A5xbgvzLzuYrbagj0t2ttfgR8ucW1PgbsSU+gdEZEPJqZ57e6cURMp8x9OQl4EYvOo9jsX5QK217BdxWoHgqcQM8CNQso34cNqn3nRMSrmkLzrYBrqjD38y1WFm/2/Ig4CNi3tm/fpjYzKd8fWEKhaEQcRwmfx/fT9FnKfKLXUKpXf5uZd1WVpA3jI2LyAG671iD7+Gp6h9PHNzV5NSUQhfIZ7BWKVouKPVVtjqKEd69vavNURNxb23ViRPw4Mwf8+c/MR4CLqxcRsTvlz239vxOrUuYWPTAirgDeVa86joiDKX8e6j/v5wM/j4gdM7Pex6EYxcD/vTkCF1CSJC1lDp+XJEkrmv3oGSoNPfM0Lks+Tc98ej/OzD8O4Jz6iu4rt21VDCjUysyHKZWiUFZPfz+wTma+KTMv6CMQhd5zi/5HX0OJW3awDJnfp7br/AFUy06tvX8zPX+X/RqwTVMg+mbg5/SEjTOB/8jMepgLQPWcb6OnknMk8N2I+EBz28ofKPM6bsSigWgCt1IWsXkXsFFmTszM19ZDr4jYhjLs//O1Pt4MbE1ZZKlRnbgD8KWme7yOEjZ9ELiteXh3NTXD1rVdP6FU7u5R2/c4JVB7P/CizHxJZh5bHav/G+GsiMi+XvQEcf19Bi6g9XQKT1MC0OOrZ1szM7fMzPdn5rcz864W5xxOWUSov9eJtXP6+3MD5Xva8CfK967ui/T8QuAVEfGyFtc4uvZ+z4h4TYs2R9HzS4DxLMY8nlXg/QN6vv8zKNWuv6z1dW3g71X7VSPia5Q/NyOrNkfTUx26HnBtRDSmMhiovwFvAF5S3W/V4ZpTlPLfv1WBNYH1gZMG2TdJkhZhpagkSVphVPPMnVDb9SQlxFhmVJVo7642nwWOG+Cp9fCtv4qq+t/xVmrbqvgGpcryh5k5mLkkb6693xn4fUT8joENl12NEn41FmR6lkWDv16qFbX3aNr9GHBQvaIzIsZQQucj6An3/grsXoXALWXmzRHxn5QQPapzT4uIlwOHZua/am0vjohr6Jm39h5KAPsz4PLMnNPHc2wDfJLei2xBCaiOyMwnqnb/QZnbMYCDq+DzQ5TP9CG1837QNLz7/yjBVCv/oIR8PwJ+0UfoPdR/I/R5XmbOjIirgVcCDwI/BC4DflV/hj6s3n+TPvVZ0RsRU+n9c/l0c4iemX+OiF/RsyDUYfQMt2+0uS4ifgzsXe06MSJeWr9WZs6NiKOBxjQNb4+IszPz0oE+TETsBPwvZRg9wELgg5nZ+LP0rYjYlDKn7pcz8+kqoP0yPVXRzwDvzcyvR8QPgWspIe26lHlVD6umw+hX9WfkxwPt/2BUvzB5mhLmP7wk7iFJ6j6GopIkaUXyZco/5hvOzcy/d6ozzSJiImXhk0Yl59cyc6CLQI1p876VehDaZ9vMfIChLaxyFaX6crNqeyt6FskZrC9m5sx+2mxL7wWc7gPeWP/+VfOHzqD38OebgT0G8jnIzO9ExCR6B+vvBHaJiK2arnEiZZGbCzPzxr6uGxGrUapG/4sy32jdw5RQ6ntNfflhRPw3PcP9pwFvpwRDjZ/vs5QAuO6r9A5F/0r5+f6QMgx9kUrZFuqfn49RqhD7MpNScdhfAA8lEH4G+M0gQ3joXWX6Xcp8sv3ZlRKQQ/+/TJhBT5D+Z8o8r62cSU8oum9EfKhayb1uOj2h6JaU6Qq+19Tmm8B7ge2q7S9FxGaZ+Xi7DkbEWpSq5v+kdzXwHym/IOj135PMvBV4W0RMjogLgLfUDv8TeEdmXl61/XNE7EkJqteg/Hn7RkTsC3ykVUV79YuobSmfy6coFeQLGNhiXfU5d1cd4HQIUD5rYygV1mOAyMyrBniuJEnPMRSVJEkrhIh4JyXAaniCRQOjjomI0cD5lDkooVTKHdv+jEXUA8H+KubqYcMqbVsthsx8NiL2olTi7kzv/g3EE5Qh+2fRM4S/r/tdVFXWfQa4E9i5aX7EI4BTmk77MbD/AKsQG/f5TESsRKnAgxLwvLU5VM3MH1KCxoF4BngjiwaiF1CqUFsGtpn5laovp1DCusYw4oavVKFX3WWUYflXUaYkuGmAfayrB+kPNi8U1Ky2eHp/YT2Z+ash9Keh/ln+S2Y2D21fRBUiNrQNRSNib3pCTIBP9RHaXkSpUl61uua7KZ/L51QLeP2UMlctwPRq0aV6tWhGxEfpWQhuCiWE/kRT39YH9qcszPRyek9T8A/KZ/VrraafiIiNgGMo04rUPzs/At5X/VKk3u/fVvOT/pie+VhfC7w6InbKzOuabvHvlArpxbUbZbqDofgHsM4w9EGS1GUMRSVJ0oriu9XXzwAvBE7IzKH+I3tJ2JwSsC2k/B3sgMycO9CTM/PblEWDBmIwAeqQVQv87N1vw+FzImVxoxOyaZX6zDw1IuZTpgN4Gvh/lGBrIJWRvWTmp6prnUKZh/Tqxel0Zj4REftQhiZvCdwEfDQz+w2TMvMLEXEHpapw7dqh3wMfadH+WcoiUItjqJ+ZNfpvslgGUonal75C25dR/nyuTplb87vtGmbm4xHxM8qcuDdRwv1WTqCEonMoi6mNoGl6icy8MiJ+TgkFH6VUWza7l1L9/Mravr9S5iH9Rj9z/z5DWZm+8b37G3BkZl7Y7oTMvLaaK/UiSpD/BPD6FoEolPlIn6SExI9V91vYR3+GQ6NSdHT1daAr3EuS1EsM4e+JkiRJy6xqiPrxwOGN+RmXJRExBXh5FXJqmEXExyjzZbYKcAZ7rW0y8/fD0K3G9bagTDfwncGGtdUw5Q9R5o/8PfA/mblguPrWdK+x9ExD8WBmzlsS9xmsql/Pqzb/VZ/ndRiv/z+UaQbO76fta4HH+hu2XU2B8K2+qpUjYhdKJeixmflgmzZjgBsoUxWcCVw20M9QtfDWlcA5wCkD/e9iVaV8NHBfZp7VX3tJkpY3hqKSJEmStIyLiBhK5fPinitJ0orKUFSSJEmSJElSV3FOUS3Xoszsvy5lpUtJkiRJkiR1tzWAB/obJWEoquXdusB9/baSJEmSJElSt3ghcH9fDQxFtbx7BODee+9l7Nixne6LJEmSJEmSOmT+/PlMmjQJBjCi2FBUK4SxY8caikqSJEmSJGlARnS6A5IkSZIkSZK0NBmKSpIkSZIkSeoqhqKSJEmSJEmSuoqhqCRJkiRJkqSuYigqSZIkSZIkqasYikqSJEmSJEnqKoaikiRJkiRJkrqKoagkSZIkSZKkrmIoKkmSJEmSJKmrGIpKkiRJkiRJ6iqGopIkSZIkSZK6iqGoJEmSJEmSpK5iKCpJkiRJkiSpqxiKSpIkSZIkSeoqhqKSJEmSJEmSuoqhqCRJkiRJkqSuYigqSZIkSZIkqasYikqSJEmSJEnqKoaikiRJkiRJkrqKoagkSZIkSZKkrmIoKkmSJEmSJKmrGIpKkiRJkiRJ6iqGopIkSZIkSZK6iqGoJEmSJEmSpK5iKCpJkiRJkiSpq4zqdAek4TBj3AzGMKbT3ZCkpW56Tu90FyRJkiRpuWOlqCRJkiRJkqSuYigqSZIkSZIkqasYikqSJEmSJEnqKoaikiRJkiRJkrqKoagkSZIkSZKkrmIoKkmSJEmSJKmrGIpKkiRJkiRJ6iqGopIkSZIkSZK6iqGoloqIGBERo5v2jY0IP4OStJjOOussNttsM8aPH8873vEOZs+e3ekuSZIkSdIyzUBKS8uewB8jYrXavlOB70TE5IjYpyO9kqTl3C9+8QsOO+wwTjnlFG6++Wbmz5/Pm970pk53S5IkSZKWaYaiaikido2IjIh1q+1XV9sZEQsj4k8R8drq2HHV/r2q7fdX2wfWLvkhYEZmPlrb9xBwP7AQ+GpEbL5UHk6SViDnnHMO73nPe9htt91Yb731OPHEE/nNb37DnDlzOt01SZIkSVpmGYqqnd2rr7vV9s0H1gReBHwBuKARmlamNn0FICJeD0Rmnh0Rp0TEK6tDC4EAHgSmATtFxEuH9zEkacU2e/ZsXvSiFz23PXLkSABGjRrVqS5JkiRJ0jLPUFTt7AZcQe9QNDPz4cx8MDPPAGYBr6qOPUNPGLpZtU1EbACcBnwgIl4OvAtYLSIOAXYFDgJuBz4IrNdfpyJidDUX6diIGAussVhPKUnLuS233JIf/ehHZCZQ5hfddtttGTduXId7JkmSJEnLLstItIiIWBvYAngj8PWIiDZNnwZWqt7/gZ5QdBPghur9DsALgAuAycDBwMTq/c3AvZm5b3XflYCt+uneMcD0QT2QJK3APvzhD7P33nuz9dZbM2bMGH77299yzjnndLpbkiRJkrRMs1JUrewG/AX4BWW4/EuaG0TEbsDGwNXVrjuAydVw+oeBx6r95wHjgXcDV2XmOZn5HeB/q3OmRsSJEfFzyjD6r0ZEX2H9DGBc7fXCoT+mJC3/JkyYwNVXX83555/P5ptvziabbMI73/nOTndLkiRJkpZpVoqqld2AazPziYi4kTK/6B+AcRHxMDAGeAJ4f2b+tSokfQa4G9gb+COwNkBmLoyINYCvAG8BiIgPAEcDM4EplKrSc4E1M/OKvjqWmU8CTza22xexSlJ3WXfddbnooos4/fTTn5tXVJIkSZLUmqGoWtkNWCsi3gSsCsyjhKKPAFtSFkh6IBsT2PX4I7AvZS7SXQEiYgxwPaUq+ZRqaP4+mfnF6vj9wJWUkPStEfHKzLxriT6dJK2ATjvtNDbZZBP22WefTndFkiRJkpZ5hqLqJSI2pcwBuj3wD2BH4GvAycCzmTmrj9P/SFk46QtUoWhVbXoa8DdKJek/MvPvtXMuBX5JCU23zcz7hvWBJKkLPPzww3z2s5/l0ksv7XRXJEmSJGm5YCiqZrsDd2bm7wAiYjbwDcqiSv35Y9NXqvlBL6QMk38FsG1E3JKZMyJiIrA+ZWGmnTLzvoiY3E/wKklqMn78eObMmdPpbkiSJEnScsOFltRsN+DyxkZmLgCuBY4fwLk3A/OBWbV9LwbupCyQtBbwTeCMiDgI+BNlWP4ngC9FxFbAtRGxy+I/hiRJkiRJktSalaLqJTNf32LfTv2cc1xtc1z19dWNHRExMTPn17a/CuwMvCszf1ntG0tZcOl3lDlJJUmSJEmSpCXCUFRLXD0QrXwQWJiZT9fafCQivg7cl5nPLtUOSpIkSZIkqasYimqpy8zH2+z/y9LuiyRJkiRJkrqPc4pKkiRJkiRJ6iqGopIkSZIkSZK6iqGoJEmSJEmSpK5iKCpJkiRJkiSpq0RmdroP0pBFxFhg3rx58xg7dmynuyNJkiRJkqQOmT9/PuPGjQMYl5nz+2prpagkSZIkSZKkrmIoKkmSJEmSJKmrGIpKkiRJkiRJ6iqGopIkSZIkSZK6iqGoJEmSJEmSpK5iKCpJkiRJkiSpq4zqdAek4TBj3AzGMKbT3ZCkpW56Tu90FyRJkiRpuWOlqCRJkiRJkqSuYigqSZIkSZIkqasYikqSJEmSJEnqKoaikiRJkiRJkrqKoagkSZIkSZKkrmIoKkmSJEmSJKmrGIpKkiRJkiRJ6iqGopIkLefOOussNttsM8aPH8873vEOZs+e3ekuSZIkSdIyzVBUS01ErBwRI5r2jYuI6FSfJGl594tf/ILDDjuMU045hZtvvpn58+fzpje9qdPdkiRJkqRlWmRmp/ug5VBEPAA8DTzVdGgUMD4zx7c45wPAvsCrM/PZat/lwHXAt4G1M/PyQfZjLDDvaI5mDGMG/RyStLz767v+ysSJEznllFMAuPXWW5k6dSqzZ89m4sSJHe6dJEmSJC098+fPZ9y4cQDjMnN+X22tFNUiIuLAiMgWrwNrzZ4C9szMDesv4NUsGpQSEaOAw4DpjUC08hBwP+WzeF5ErLOknkuSVkSzZ8/mRS960XPbI0eOBGDUqFGd6pIkSZIkLfMMRdXKd4A1a69JwGzg17U2zwArR8SY+gsYDbQaDn8IcA1wRUScGRGbVvsXVu1vBQ4A9o+IyUvgmSRphbTlllvyox/9iMbIj7POOottt9228dtRSZIkSVILlpFoEZn5FLVqz4h4P3BRZt5Va/YAcH6bS9xX34iIbYAPA68A3g68EvhOROwKbA28FngfcAtwBzCyXd8iYjQleG1YY2BPJUkrpg9/+MPsvffebL311owZM4bf/va3nHPOOZ3uliRJkiQt0wxF1aeq+vNwYLv6/szccRCX2QN4HvALYGNgF2ALYAIwE7g7Mz9Su9+mba4DcAwwfRD3lqQV2oQJE7j66qu58847Oemkk5g7dy7vfOc7O90tSZIkSVqmGYqqP+8Ers3MWRExBbgRWEAZ9j6GstjS0y3OG0mp4twc+Bwwg7LI0q6ZeSVwZbVI0nHADhHxeWArYCrwO2DPNv2ZAZxc216DpspUSepG6667LhdddBGnn376c/OKSpIkSZJaMxRVf95LVZlZDZ9/bpK6iLgTOCgzr+rvItU8ocdShs4TEScCbwFmAZOBU4BvAqMy87p218nMJ4Ena9cd5ONI0orptNNOY5NNNmGfffbpdFckSZIkaZlnKKq2ImJDYEPKsPfmYy8EXgC0DTBrbSdV7eYA50bE6sBumXlURKxCmZ/0EuBcYOOI2Ckz5wzfk0jSiu3hhx/ms5/9LJdeemmnuyJJkiRJywVDUfVlX+AnmbmwxbHtgEeB+1tUa04EtszMm6vtB4FTKSvMzwIerBZzIjMfj4gbgOuBucAOmTlvmJ9DklZo48ePZ84cf5ckSZIkSQM1otMd0DJtD+BXrQ5k5oWZuVbzC9iWsnL9rbXmI4DvAY8BuwFfjIgDASJiPWBtYCPgnZk5rxpqL0mSJEmSJC0RhqJqqRrWvh3w2wG0XSsipkbEVOAw4Kam6tKdgdsoK8ePAk4DLo6IIykVomcDZwBnRsTLgNurofuSJEmSJEnSsHP4vFrKzMeB0QNsPgm4AZgH3EFZUKl+rcsiYmJmPgIQZbz9TynD7HfPzBsiYhRloaXfAxdk5p3D8ySSJEmSJElSb4aiWmyZeWNEjG7ME9qmzSO19xkRb8vMBbV9TwP7RcQM4PYl22NJkiRJkiR1M0NRDYu+AtE27Re02T9zeHokSZIkSZIkteacopIkSZIkSZK6iqGoJEmSJEmSpK5iKCpJkiRJkiSpq0RmdroP0pBFxFhg3rx58xg7dmynuyNJkiRJkqQOmT9/PuPGjQMYl5nz+2prpagkSZIkSZKkrmIoKkmSJEmSJKmrGIpKkiRJkiRJ6iqGopIkSZIkSZK6iqGoJEmSJEmSpK5iKCpJkiRJkiSpq4zqdAek4TBj3AzGMKbT3ZCkrjc9p3e6C5IkSZLULytFJUmSJEmSJHUVQ1FJkiRJkiRJXcVQVJIkSZIkSVJXMRSVJEmSJEmS1FUMRSVJkiRJkiR1FUNRSZIkSZIkSV3FUFSSJEmSJElSVzEUlSRJkiRJktRVuiIUjYiVI2JE075xERFL6H6rNG1HRIwbxPmjI+KjTfsmDKEf74iIQwZ7Xh/XGxkRq1fvW37vWjz76hExsk3b3SPi5cPVP0mSJEmSJGkglrtQNCIeiIi/RcSdTa9ZEfFwm9MOBq5oCkZ/AMyIiJdExC4DvPf9ETF1AE2/FRGfqp8KzImIPSLijRGxfj/nfxUYVbtvAHdGxCsH0s+afwGnRcQrqus8FRHZ4vXf9ZMi4ucR8aYW11sbmBcRawN/jojNms7bDLgnIv6ttvtI4OqIWCsi9m+63n3AWRGxziCfS5K0jJszZw7rr78+s2bNem7fzJkz2WabbVhzzTU56qijyMzOdVCSJElSV+tYKBoREyPi7oiY3Ob4pRFxYItDTwF7ZuaG9Rfw6upY83VGAYcB0zPz2dqhh4D7Kd+D85qDuYgY06LC8XHgiaZ2K9fbRcQGwCuAzzf2VfedU93v36r7tau03BV4YWZ+urZ7K+DvmfmbprZvi4gjml6b1u57GXA+8JZq11PAdsAqtddVwMKmbjxWPWuzh4HHM/MhYAawRdPxDwFfzswHa/sa3+cngE9GxJ61/t0KfBo4odX3QpK0fJo9ezZ77bVXr0D0ySefZO+992brrbfmD3/4A7feeitnn312x/ooSZIkqbt1JBSNiLWAnwCT2xzfD3htm9OfAVauQsvnXsBoSkVms0OAayiVomfWQsOFVftbgQOA/ZsC2vuAf0XE7Mar6u/va/vmAHPpCR2hBHzHAGMi4qyIGNt0v3OBk4FPtHm+44APN+17OzA5IuZGxPyIeDgiPgm8F9gaeLp6/Tfw0qZzjwAaQ/GfAZ7KzCcaL+DZ6lX3XOlORFxS3e9h4O/AatX7LwDfiIjnV+22oASuMyLi4xHxxqbnfhT4D2DdKvhtOBfYbADVs5Kk5cS0adOYNm1ar32XXHIJ8+bN4+STT2aDDTbg+OOP5xvf+EaHeihJkiSp243qv8kScV712r75QDV35ueAP7c59wFK9WMr9zVdaxtKwPgKSrD4SuA7VSi3NSV4fR9wC3AH8FzFZ2au1aJvtwN7ZOasVjePiPcDawHfq55hFeDVVRA7HriYUjn5J+CvEbFyZj5VO//5wBqZeXNt30rAfpTAcTvg1Zm5f3XsYuCXmXl2tf1W4MlqmoBVMvPRzJxd62Kf4xQjYk1KBehLgPdX4fVKwD6ZeUXV5mHghZTKz5WAJ6rh9OdSKnJfABwFHBgR7wbeDOxI+f7eQfm5/vW5DmVmRJxXtftcX/2r7j+aEoA3rNHfOZKkpev0009nypQpHHHEEc/tu/nmm9l+++1ZddVVAdh888259dZbO9RDSZIkSd2uU6HowZl5V0Sc2uLY5yjzfa7S4hiZueMg7rMH8DzgF8DGwC6UId8TgJnA3Zn5ESjD5YFN6ydHxMjMfGYQ93sLsDkl9BwHbAL8D3AXMAv4SGb+tLr2RGB9eoe/LwH+0HTNHYDrMvNPEbEjvacIaBVyJmWI/q3VCP3HMrMxx2d/C0s9CVxNqTa9hRJeNj//HGDNql8jM/M7EbFJ9axfpXy/TwIeAXYCbgLWysxtq+ceAWwVEStlZmPY/rWUeV8H4hhg+gDbSpI6YMqUKYvsmz9/Puuv3zMoICIYOXIkc+fOZc0111ya3ZMkSZKkzgyfz8y7Wu2PiJ2BXekZ7t3YPyUi5lULHc2KiL9HxH3V++bXvdVw7xdRAtZxwKeAszPzysz8AmX4+r3ADhHx+Yj4NWXey0/R2xer+8yNiJmUwPEnETEzIhZGxG5N7d+UmROBy4EjM3NOZn4A+A5lPs53RsQ3IuIm4DZgWtP5awP/bNp3NfC26v1EYEFEjIiIlVt9DwEy8/7MHFd9L+sharuf94jqvMcy81uUatwrM/O31bEfRsSCKItH/Z1SDbsbsGV13lVV33YH7gROyMxfUH6ONwGTIuL4qrL1QeAcSnja8FDTdl9mUH6mjdcLB3ieJKmDRo0axejRo3vtGzNmDI899liHeiRJkiSpm3WqUnQRVaXm14D3Zeb8+jpEVYg6rtb2TuCgKozr77qTgWMpQ+eJiBMpFZ2zKHOEngJ8ExiVmdfVz83M90XE/1CqN1+VmXOqa7wBOC4zf97Ufn5E7A2sl5kHV22vpVS9PkOp4DyRMtT8tsz8e1N3F7DocPATgXdHxNPVsaeAdwH30DRdQBv1atKRwK8iol79uTpluH87K1OmGdixeo57gKnAvwMfr7V7CjgbOCwzn6q+D18HbqZMHXAP8H3gedUCUHVrUJ69/4fJfJJS0QqUSiNJ0rJvwoQJzJw5s9e+Rx55hJVXbvs7PkmSJElaYjq2+nwLnwB+n5kX99UoIl5Imbfyur7aVW0nVe1GAOdGxJXAsZk5BXg9sBpwCSXcO6sa0t5LFVx+m6qKNCJWo1SgHtHifm8ALgBWiYifRcQXgJ0ycwtK1eQzwA3AGcApLVagvwfoNeYwMz+YmeOqCtS/UOb3XDMzt+zv+Wv9imq4+qrVuWtVc6aunZljMvMrfZy+FjCfEo4+SZl24BWU4fLX1Nr9ijL9wIcj4mpKYLtOZu5ePfOfgJ2B8yNiu6Z7TKmeXZK0gtpmm2249tprn9ueNWsWTz75JBMmTOhgryRJkiR1q2WmUhR4J7B2tZAPwKrAvhGxbWa+v9ZuO8pK5ve3qBKcCGxZW6joQeBUygrzs4AHGwsbZebjEXEDcD1lBfkdMnNem779D3B1RBxBGZJ+YWb+ukW724GPVF/vBe6vLaT0G0pF5tXApcChmdk8J+ifgI0jYvXM7FU5GRGbUSpbp0fEnzPz3jZ9beXTwD8j4svAL4EjMvN64EcRcU5mfr92n3GUOUOnR8RrKPOezqJUiT5ECTh/DlxSVW02fIPyc7mL8n2/r/Z8l1bH1wRemZl/aurf3pQqU0nSCmqnnXZi3rx5nHPOORxwwAGccMIJvOY1r2HkyJH9nyxJkiRJw2xZqhTdEdiMMk/llsCPgE9Wr+dk5oWNSsf6C9iWMoS7vpTtCEoQ+RhlDswvRsSBABGxHmUOz42Ad2bmvGqo/SIy8zFKpegplIWaPtPmGR6kLOq0KmW+0POrMBNge3q+34cCo6vV5uv3Scp8mx9qce3PVn04GfhNtaL9COCkxnyqTfdoPP8k4L3AFcD/q/p2S3X8UuCciNi++p6sS1lI6RHg89X73wD7Af9BCXqfBMYAF0fE5IhYtVo86ZLq+FaUhZBOrq65CqWCdBPgqGrBqMmNDkbERpQFpq5o/S2VJK0IRo0axemnn8573/tenv/853PBBRdwwgkndLpbkiRJkrrUMlMpmpm95seMiAXA7Myc3e6ciFgLaASL/wXcVFvRHMpw7R9TqjN/BpwG3BYRRwIfA46nhKJnRsRHKGHjZpl5Z3X99SkrqL8dWAd4A/Aaysru/0cZMv5n4O/VMPuPAe+jBKOXU4bMz68qNPcB9gf+lzJP6EzguIiYkpnP1vp8IvD7iLg4M/9Q9eNgYF3g5Gq+zomUitnRwIcz8+yq3RXVvoY3U0LMPYANgfcA22TmE9X3/EsRsTXwg4jYOjMfiIgNMvOeapqCLwL7UuZznUFZZOknwJmUKQd2Bv5VPdNtwN3AZcAPgOsi4k2UMPea6t7HV/PBfqWaWuDblArSj2Rm8yr3kqTlXPOAiH322Yc77riDP/zhD+ywww6svfbaHeqZJEmSpG7X0VA0M9uukpOZBw7gEpMow7nnAXdQFlSqX+OyiJiYmY9AmVsT+CnVSumZeUNEjKIstPR74ILMvDMiVqVUSL6wav+5zPxlddkfR8QJlMrJ9wKbA8cAp1MqMT+RmU9X95tAGRL/a2CrzPxHRFxPqar8EPCBpkC0Max/GmXe0tdGxIbAccArakP/v15d/xnK6u4NH6JUqzacT5lT9R+UYfP7ZObdTd/DQ6s2OwLfy8zG3J7TKdMEXF7day9K0Ht4Zp4eEcdRqnhfnZkPRcQLM3N+46IRcXR17Q9l5nnVvlWBq4C/URZd+g/gl5n5MyRJXeEFL3gBL3jBCzrdDUmSJEldLhad1nL5EhEr1+btHEj7RebrrPZvBtxeCzRXy8xHh6F/azRC2dq+lYCNMvOWNqcRESMb1ZMRMbYeOA6xHxtl5l/aHBvTqB6t7QtgVKPyttreODNvr7WZ1G5u0ypsXikzH2/avx4wPzPnVsPus8XcqoN5rrHAvKM5mjGMGeplJEnDZHpO73QXJEmSJHWp+fPnM27cOIBx/WVpy8zw+aEaTCBatV8kEK32z2zaXuxAtLrOIy32LaRnXs925z1Te79YgWh1jZaBaHXsiRb7EljYtH17U5u2iz1V4fLTLfbfU3v/bPNxSZIkSZIkaUlblhZakiRJkiRJkqQlzlBUkiRJkiRJUlcxFJUkSZIkSZLUVQxFJUmSJEmSJHWV5X71eXW3xurz8+bNY+zYsZ3ujiRJkiRJkjpkMKvPWykqSZIkSZIkqasYikqSJEmSJEnqKoaikiRJkiRJkrqKoagkSZIkSZKkrmIoKkmSJEmSJKmrGIpKkiRJkiRJ6iqjOt0BaTjMGDeDMYzpdDckScuY6Tm9012QJEmStAyyUlSSJEmSJElSVzEUlSRJkiRJktRVDEUlSZIkSZIkdRVDUUmSJEmSJEldxVBUkiRJkiRJUlcxFJUkSZIkSZLUVQxFJUmSJEmSJHUVQ1FJkiRJkiRJXcVQVEtNRKwcESOa9o2LiOhUnyRJ3WHOnDmsv/76zJo1a0D7JUmSJK3YRnW6A1o2RcREYGPgL5k5u8XxB4CngaeaDo0Cxmfm+BaXPRjYNyJenZnPVvt+AFwXEd8G1s7My4frGSRJApg9ezZ77733IsFnu/2SJEmSVnxWina5iJgYEXdHxOTavmnAncCXgL9V282eAvbMzA3rL+DVLBqUEhGjgMOA6bVAFOAh4H7KZ/G8iFhnmB5NkiQApk2bxrRpi/6vrN1+SZIkSSs+Q9EuFhFrAT8BJtf2jQdOA3bMzK2AQ4DPtDj9GWDliBhTfwGjgVbD4Q8BrgGuiIgzI2LTav/Cqv2twAHA/vWAVpKkxXX66adz+OGHD3i/JEmSpBWfw+e723nVa/vavjWAIzJzZrV9M7Bmi3MfAM5vc9376hsRsQ3wYeAVwNuBVwLfiYhdga2B1wLvA24B7gBGtutwRIymBK/1/kqS1NaUKVMGtV+SJEnSis9QtLsdnJl3RcSpjR2ZeS/wbYCIWIkSZl7UfGJm7jiI++wBPA/4BWWe0l2ALYAJwEzg7sz8SHXPMcCmba4DcAwwfRD3liRJkiRJknoxFO1imXlXu2MRsQXwK8r8oJtU+6YANwILKMPex1AWW3q6xSVGUqo4Nwc+B8wA9gV2zcwrgSsjYixwHLBDRHwe2AqYCvwO2LNN12YAJ9e216CpMlWSJEmSJEnqi6Go2vkjsCtwEnAW8KYqRB3XaBARdwIHZeZV/V2smif0WMrQeSLiROAtwCzKnKanAN8ERmXmde2uk5lPAk/Wrju4p5IkSZIkSVLXMxRVS5mZwI0RcSBwT0SsmZlzG8cj4oXAC4C2AWat7aSq3Rzg3IhYHdgtM4+KiFUo85NeApwLbBwRO2XmnGF/KEmSJEmSJAlDUTWJiF2A12XmUdWuxtD4Z5uabgc8CtzfolpzIrBlZt5cbT8InEpZYX4W8GBmPgWQmY9HxA3A9cBcYIfMnDdsDyRJkiRJkiQ1MRRVs9uBH0bEHZTqzU8BP2sOKjPzQuDC5pOreUdvowSgDSOA7wEbALsB20bExZl5dkSsB6wNbARskJnzImJyZs4a/keTJHWzMghi4PslSZIkrbhGdLoDWrZk5gPA24AjgFuAVYF39XVORKwVEVMjYipwGHBTZi6sNdmZEpQeQwniTwMujogjKRWiZwNnAGdGxMuA2yNiw+F8LkmSJEmSJKnBSlGRmdG0fRmw6SAuMQm4AZgH3EFZUKnX9SJiYmY+AhBlvP1PKcPsd8/MGyJiFGWhpd8DF2TmnUN9HkmSJEmSJKkvhqJabJl5Y0SMbswT2qbNI7X3GRFvy8wFtX1PA/tFxAzKEH5JkiRJkiRpiTAU1bDoKxBt035Bm/0zh6dHkiRJkiRJUmvOKSpJkiRJkiSpqxiKSpIkSZIkSeoqhqKSJEmSJEmSuoqhqCRJkiRJkqSuEpnZ6T5IQxYRY4F58+bNY+zYsZ3ujiRJkiRJkjpk/vz5jBs3DmBcZs7vq62VopIkSZIkSZK6iqGoJEmSJEmSpK5iKCpJkiRJkiSpqxiKSpIkSZIkSeoqhqKSJEmSJEmSuoqhqCRJkiRJkqSuMqrTHZCGw4xxMxjDmE53Q5K0jJme0zvdBUmSJEnLICtFJUmSJEmSJHUVQ1FJkiRJkiRJXcVQVJIkSZIkSVJXMRSVJEmSJEmS1FUMRSVJkiRJkiR1FUNRSZIkSZIkSV3FUFSSJEmSJElSVzEUlSRJkiRJktRVDEW11ETEyhExomnfuIiITvVJktQd5syZw/rrr8+sWbMGtF+SJEnSim1Upzug5VNEPAA8DTzVdGgUMD4zx7c47WBg34h4dWY+W+37AXBdRHwbWDszL19SfZYkdafZs2ez9957LxJ8ttsvSZIkacVnpahaioiDImJmRDwcEd+NiLWamjwF7JmZG9ZfwKtZNCglIkYBhwHTa4EowEPA/ZTP4nkRsc4SeSBJUteaNm0a06ZNG/B+SZIkSSs+Q1EtIiJeA3wB+CCwBTCWUtFZ9wywckSMqb+A0UCr4fCHANcAV0TEmRGxabV/YdX+VuAAYP+ImDzczyRJ6l6nn346hx9++ID3S5IkSVrxOXxerRwAfD0zfw4QEUcBt0TExMycU7V5ADi/zfn31TciYhvgw8ArgLcDrwS+ExG7AlsDrwXeB9wC3AGMbNexiBhNCV4b1hjco0mSus2UKVMGtV+SJEnSis9QVK2sBdxY236m+vp0Y0dm7jiI6+0BPA/4BbAxsAulAnUCMBO4OzM/AlBVm27a5joAxwDTB3FvSZIkSZIkqRdDUbVyE/CGiDg1MxM4CLgOmBgRfwMWUIa9j6EEpU+3uMZIShXn5sDngBnAvsCumXklcGVEjAWOA3aIiM8DWwFTgd8Be7bp2wzg5Nr2GjRVpkqSJEmSJEl9MRRVKycBPwauj4gngJcDB2TmXcC4RqOIuBM4KDOv6u+C1Tyhx1KGzhMRJwJvAWYBk4FTgG8CozLzunbXycwngSdr1x3ck0mSJEmSJKnrGYpqEZn5L+AVEbEhZS7QNYHv1NtExAuBF1AqSPsUEZOqdnOAcyNidWC3zDwqIlahzE96CXAusHFE7FSbu1SSJEmSJEkaVoai6ssDwJuBgzPzmaZj2wGPAve3qNacCGyZmTdX2w8Cp1JWmJ8FPJiZTwFk5uMRcQNwPTAX2CEz5w3/o0iSJEmSJEmFoaj6cihwe2b+sPlAZl4IXNi8PyKmALdRAtCGEcD3gA2A3YBtI+LizDw7ItYD1gY2AjbIzHkRMTkzZw33w0iSuluZJnvg+yVJkiStuEZ0ugNaNkXEeOAjwIcG0HatiJgaEVOBw4CbMnNhrcnOlKD0GEoQfxpwcUQcSakQPRs4AzgzIl4G3F4N3ZckSZIkSZKGnZWiaikzH6YMgx+IScANwDzgDsqCSvVrXRYREzPzEYAo4+1/Wl1/98y8ISJGURZa+j1wQWbeOSwPIkmSJEmSJDUxFNViy8wbI2J0Y57QNm0eqb3PiHhbZi6o7Xsa2C8iZgC3L9keS5IkSZIkqZsZimpY9BWItmm/oM3+mcPTI0mSJEmSJKk15xSVJEmSJEmS1FUMRSVJkiRJkiR1FUNRSZIkSZIkSV3FUFSSJEmSJElSV4nM7HQfpCGLiLHAvHnz5jF27NhOd0eSJEmSJEkdMn/+fMaNGwcwLjPn99XWSlFJkiRJkiRJXcVQVJIkSZIkSVJXMRSVJEmSJEmS1FUMRSVJkiRJkiR1FUNRSZIkSZIkSV3FUFSSJEmSJElSVxnV6Q5Iw2HGuBmMYUynuyFJ0nJjek7vdBckSZKkjrFSVJIkSZIkSVJXMRSVJEmSJEmS1FUMRSVJkiRJkiR1FUNRSZIkSZIkSV3FUFSSJEmSJElSVzEUlSRJkiRJktRVDEUlSZK0iDlz5nDNNdcwe/bsTndFkiRJGnaGopIkSV1szpw5rL/++syaNeu5feeddx4bbrgh//3f/82LXvQizjvvvM51UJIkSVoCDEW11ETEyhExomnfuIiITvVJkqRuNnv2bPbaa69egejDDz/MoYceylVXXcWNN97I1772NT760Y92rpOSJEnSEmAoqiGJiAci4m8RcWfTa1ZEPNzmtIOBK5qC0R8AMyLiJRGxyxLvuCRJes60adOYNm1ar32PPPIIp556KpttthkAW2yxBXPnzu1E9yRJkqQlxlC0y0XExIi4OyImtzl+aUQc2OLQU8Cemblh/QW8ujrWfJ1RwGHA9Mx8tnboIeB+ymfxvIhYZ7EeSJIkDdjpp5/O4Ycf3mvfpEmT2G+//QBYuHAhJ510Em9+85s70T1JkiRpiRnV6Q6ocyJiLeDHwOQ2x/cDXgu0mkjsGWDliBjTtH800Go4/CHANZRK0TOBkzLzVmBh1f5W4ABg/4i4IDNnDfqBJEnSoEyZMqXtsZtvvpmdd96ZlVdemdtvv30p9kqSJEla8qwU7W7n0TrwJCImAJ8D/tzm3AeA84GZTa+LgfuarrUN8GHgY8DbgVcC60bEocDWwCeAPwLvASYCI9t1OCJGR8TYxgtYY0BPKkmSBmXzzTfnl7/8JVOnTuWggw7qdHckSZKkYWWlaHc7ODPviohTWxz7HGW+z1VanZiZOw7iPnsAzwN+AWwM7AJsAUygBKl3Z+ZHAKrK0037uNYxwPRB3FuSJA1BRLDVVltx9tlns9566zF37lzWXHPNTndLkiRJGhZWinaxzLyr1f6I2BnYFfho0/4pETEvIu6vFlT6e0TcV71vft0bEQ9HxIsoAes44FPA2Zl5ZWZ+ATgZuBfYISI+HxG/pswv+qk+uj2julbj9cLF+y5IkqS6yy+/nKOOOuq57VGjyu/QR4zwr42SJElacVgpql6qSs2vAe/LzPkRPdODViHquFrbO4GDMvOqAVx3MnAsZeg8EXEi8BZgFmVO01OAbwKjMvO6dtfJzCeBJ2vXHfCzSZKk/m2yySbss88+vPjFL+Z1r3sdH//4x9l9990ZN25c/ydLkiRJywl/5a9mnwB+n5kX99UoIl4IvABoG2DW2k6q2o0Azo2IK4FjM3MK8HpgNeAS4OPAWRExcfEeQZIkDdW6667L97//fU499VSmTp3KY489xre+9a1Od0uSJEkaVlaKqtk7gbUj4uFqe1Vg34jYNjPfX2u3HfAocH+Las2JwJaZeXO1/SBwKmWF+VnAg5n5FEBmPh4RNwDXA3OBHTJz3nA/lCRJai8ze22/9rWv5dZbb+1QbyRJkqQlz1BUzXak9+fiJOBa4Ox6o8y8ELiw+eSImALcRglAG0YA3wM2AHYDto2IizPz7IhYD1gb2AjYIDPnRcTkzJw1bE8kSZIkSZIk1RiKqpfMvK++HRELgNmZObvdORGxFvD8avO/gJsyc2Gtyc7Aj4GrgZ8BpwG3RcSRwMeA4ymh6JkR8RHgNxGxWWbeOUyPJUmSJEmSJD3HUFRkZtvVijLzwAFcYhJwAzAPuIOyoFL9GpdFxMTMfAQgynj7n1KG2e+emTdExCjKQku/By4wEJUkSZIkSdKSYiiqxZaZN0bE6MY8oW3aPFJ7nxHxtsxcUNv3NLBfRMwAbl+yPZYkSZIkSVI3MxTVsOgrEG3TfkGb/TOHp0eSJEmSJElSayM63QFJkiRJkiRJWpoMRSVJkiRJkiR1FUNRSZIkSZIkSV3FUFSSJEmSJElSV4nM7HQfpCGLiLHAvHnz5jF27NhOd0eSJEmSJEkdMn/+fMaNGwcwLjPn99XWSlFJkiRJkiRJXcVQVJIkSZIkSVJXMRSVJEmSJEmS1FUMRSVJkiRJkiR1FUNRSZIkSZIkSV1lVKc7IA2HGeNmMIYxne6GJElaQUzP6Z3ugiRJkpYgK0UlSZIkSZIkdRVDUUmSJEmSJEldxVBUkiRJkiRJUlcxFJUkSZIkSZLUVQxFJUmSJEmSJHUVQ1FJkiRJkiRJXcVQVJIkSZIkSVJXMRSVJEmSJEmS1FUMRZchEbFyRIxo2jcuImIQ1zgiIsYOf+8GJyI2GECbsRHxwaXRH0mSpKGYM2cO66+/PrNmzXpu36GHHkpEPPfacMMNO9dBSZIkDYmh6GKIiIkRsUNErNXi2AMR8beIuLPpNSsiHm5zyYOBK5qC0R8AMyLiJRGxSz/9+Q9gD+DRFsc+FxEnVO+PiYgz21xjpYhYqY97vDgiPhARV0fEzk3H9ouIr0bELcCvI2JCROwREY9Xzz03Ij5bO+VR4LVVvyVJkpYps2fPZq+99uoViAJcf/31XHzxxcydO5e5c+dy4403dqaDkiRJGjJD0SGKiGnAncCXgL9V23VPAXtm5ob1F/Dq6ljz9UYBhwHTM/PZ2qGHgPspP6vzImKdNv1ZCzgWeEdmPtOiyULgier94636UDkCuCsiZkfEPyNi1Yg4MyL+EBH/Am4F/gP4aYtzDwD+DuyRmS/IzH9V+6/MzMnAZ6p7A1D18x3AxyJiQpv+SJIkdcS0adOYNq33X/GefvppZs6cyU477cT48eMZP348a6yxRod6KEmSpKEyFB2CiBgPnAbsmJlbAYdQAr+6Z4CVI2JM/QWMBloNhz8EuIZSKXpmRGxa7V9Ytb+VEjruHxGTW5x/OPClzJw7hOeZ2KhOzcwTM3MS8D3gC5n5GDADeBvwPOCy6j6fzsxfNV3qCWBmZt5bG/K/OjC71ibrJ1T9/TIlEJYkSVpmnH766Rx++OG99v3pT38iM9lyyy1ZZZVV2GOPPfjb3/7WoR5KkiRpqAxFh2YN4IjMnFlt3wys2dTmAeB8YGbT62LgvnrDiNgG+DDwMeDtwCuBdSPiUGBr4BPAH4H3ABOBkS36tA/w3abrju5vPtKIeGV17Q/X9k0A3koJKwHeSQlCn+7rWpTA80sRcT/weESMpIS9v6mOzwfeFhEnRsS2tfO+C7ypn2vXn2ls40X5WUiSJA27KVOmLLLv1ltvZerUqXz3u9/l1ltvZaWVVuKQQw7pQO8kSZK0OEZ1ugPLo8y8F/g2lDk4KYHiRU1tdhzEJfegVGH+AtgY2AXYAphACVLvzsyPVPcbA2xaP7nqw+jM/GfTde8DRkREAqsC9fk814mIs4HXAJ8Gvl47diLww9rw9yeAx2rHj4iIfYG/ZOYRTff878y8oOrXi4CngW9Wx74JzAVWA+5pnJCZ/4yIVSJi1ACC12OA6f20kSRJWiL2228/9ttvv+e2v/jFLzJlyhTmz5/P2LEdX+tSkiRJA2QouhgiYgvgV5T5OTeJiCnAjcACyrD3MZRQsFXQN5JS5bg58DnKEPV9gV0z80rgyqoS8jhgh4j4PLAVMBX4HbBn7Vpr0XuIOgCZuXatryc0HX45cALwvsx8vNZuBPCK8jaeAHalTAXweO3cG4FrW92zdo0xlMrQc4G9qmCW6vvy88z8R9Npc6rn+Hura9bMAE6uba9BU+WtJEnS0jJ+/HieffZZHnzwQUNRSZKk5Yih6OL5IyU0PAk4KzPfBIxrHIyIO4GDMvOq/i5UzRN6LGXoPBFxIvAWYBYwGTiFUmk5KjOvazp9AYMfRv6DzDylxf6VKJWrf6cs8HQ9JUCtL950ZWae3ea6ZwGnU+ZOfTE9Q/4bCzMdCWxLrVK0skb1HH3KzCeBJxvb/cwOIEmSNKyOPPJItt9+e/bdd18Afv/73zNixAgmTZrU4Z5JkiRpMAxFF0NmJnBjRBwI3BMRazYWOoqIFwIvAJoDzEVExKSq3Rzg3IhYHdgtM4+KiFUo85NeQqm63DgidsrMObV+PBIRawxw+Hl/Xgp8hzLU/rrMfKKaG7RVv1vd76DG8PmqzX8Cl1OGvb8SeGNm3tR8HWC1zOw3FJUkSeqkLbfckmOPPZZ11lmHp59+mkMPPZQDDzyQVVddtdNdkyRJ0iAYig5BROwCvC4zj6p2NYLBZ2vNtgMeBe5vUc04EdgyM2+uth8ETqWsMD8LeDAznwLIzMcj4gZKxeZcYIfMnNeiW9cArwJ+OfQng8z8bUR8l7LI0kG1Q2+IiNmUxbl2iIjTqudbp9YmgKkRsRawJXBiZv41ImZRql73p/fQ94ZX0bMYkyRJ0jLrgAMO4LbbbuONb3wja6yxBm9605s4/vjjO90tSZIkDZKh6NDcDvwwIu6gVHB+CvhZPazMzAuBC5tPrOYdvY0SgDaMAL4HbADsBmwbERdn5tkRsR6wNrARsEFmzouIyZk5q+nSX6XMP/rL6j5BGb7+CmBn4HXAl1o9TLXa/MuBy6rKz99Whw6IiMsy8zPAZ/r6hkTEdZQ5T9es+vAzSoUrlGkBfg78CTizxenHAp/o6/qSJEmdUgYH9ZgxYwYzZszoUG8kSZI0HEZ0ugPLo8x8AHgbcARwC2Vl93e1ax8Ra0XE1IiYChwG3JSZC2tNdqYEpcdQgurTgIsj4khKhejZwBnAmRHxMuD2iNiwqU+/Bv4eEf9d7ZoG3ExZkOkK4CeUSk4oc3JuWg3NB3gTZb7SlSJiE8ow/XdRFnS6IyJOj4i9I+LfqkWUiIhR1fbm1TV2pcwb+oXM/J/MvKi63v6UqtPrgEnACRGxW0SMr67z35TK2Kvbff8kSZIkSZKk4WSl6BBl5mXApgNsPgm4AZgH3EGpjOx1rYiYmJmPwHNVnj+lDLPfPTNvqObd/Cbwe+CCzLyzxX0OAS6rhr9/j7LK++zqmltQVoSnuvbBwL3V0P4ngMOqofr/SVk06tzqvDOB/YDDKZWna1ZhauOzczZlHtFHqv2rVudtRKkY/SlwQGbeHBEvAA4FvgKcXPVzf2D3AX4fJUmSJEmSpMUWzcOBtGRExMqNeUIH2H71VgsPRcRmwO3tFlSKiJGZ+UyrYwO8b1A+F8/2024kZa2ptu0iIrLNB6xxbBj6OxaYdzRHM+a5zFeSJGnxTM/pne6CJEmSBmn+/PmMGzcOYFxmzu+rrZWiS8lgAtGqfcuV2DNzZj/nDTlgrM5PoN+kfCD3aReI1o8tbn8lSZIkSZKkwXJOUUmSJEmSJEldxVBUkiRJkiRJUlcxFJUkSZIkSZLUVQxFJUmSJEmSJHUVV5/Xcq2x+vy8efMYO3Zsp7sjSZIkSZKkDhnM6vNWikqSJEmSJEnqKoaikiRJkiRJkrqKoagkSZIkSZKkrmIoKkmSJEmSJKmrGIpKkiRJkiRJ6iqGopIkSZIkSZK6yqhOd0AaDjPGzWAMYzrdDUmSpGE3Pad3uguSJEkrHCtFJUmSJEmSJHUVQ1FJkiRJkiRJXcVQVJIkSZIkSVJXMRSVJEmSJEmS1FUMRSVJkiRJkiR1FUNRSZIkSZIkSV1lyKFoRHymj2MHDfW6kiRJkiRJkrQkLU6l6G7NOyLiZRExEjhkMa4rSZIkSZIkSUvMgEPRiLgzIv4UEbdFxJHAvIh4b0TMj4i5EfF/wBeB0cDjS6rDWn5FxMoRMaJp37iIiE71SZIkaXkxZ84c1l9/fWbNmrXIsaOPPpq999576XdKkiRpOTVqEG1nU0LUzwBbAgur7UOB9wG3Amtm5mNmXCuGiJgIbAz8JTNnNx17AHgaeKrptFHA+Mwc3+KSBwP7RsSrM/PZat8PgOsi4tvA2pl5+XA+gyRJ0opg9uzZ7L333i0D0ZkzZ/LlL3+ZG2+8cel3TJIkaTk1mOHzjwNPAPc27X+YEpA+PUx90jIgIqYBdwJfAv5Wbdc9BeyZmRvWX8CrWTQoJSJGAYcB02uBKMBDwP2Uz+J5EbHO8D+NJEnS8m3atGlMm9b81zHITA455BCOOOIINthggw70TJIkafk0HKvPN6pNRwARESsPwzXVQRExHjgN2DEzt6LMEdu8sNYzwMoRMab+okyf0KpU+BDgGuCKiDgzIjat9i+s2t8KHADsHxGTh/uZJEmSlmenn346hx9++CL7zzjjDG666SbWX399fvKTn7Bw4cIO9E6SJGn5M5jh860E8E1gZeBlwEjgH0Au5nXVWWsAR2TmzGr7ZmDNpjYPAOe3Of+++kZEbAN8GHgF8HbglcB3ImJXYGvgtZQpGG4B7qB8jlqKiNGU4LXeV0mSpBXalClTFtm3YMECPv7xj/PiF7+Y++67j29961t8+tOf5le/+hVjxozpQC8lSZKWH4sbiiawHyXwugJ4VWbuFBG/WtyOqXMy817g2wARsRLl53tRU5sdB3HJPYDnAb+gzFG6C7AFMAGYCdydmR+p7jcG2LTNdQCOAaYP4t6SJEkrpIsuuohHH32Uyy+/nAkTJnDMMcfwkpe8hHPOOYeDDz64092TJElapi1uKNpgZegKKCK2AH5FmSN0k4iYAtwILKAMex9DmUu21XyyIylVnJsDnwNmAPsCu2bmlcCVETEWOA7YISI+D2wFTAV+B+zZplszgJNr22vQVJkqSZLUDe677z622247JkyYAMCoUaPYfPPNufvuuzvcM0mSpGXfYELRcZR5Qzdv2j8ZWI0SkGnF8kdgV+Ak4KzMfBPlcwBARNwJHJSZV/V3oWqe0GMpQ+eJiBOBtwCzKJ+hUyhTMYzKzOvaXScznwSerF13kI8kSZK0Ypg0aRKPP/54r3333HMPO++8c4d6JEmStPwYzEJLTwBzKMPl7wVWAR6jrCg+FlgHWCki1sLK0RVCFjcCBwJvjIjn5hWNiBcCLwDaBpi1tpOqdiOAcyPiSuDYzJwCvJ4Sql8CfBw4KyImDvezSJIkrWhe//rXc9ttt/HVr36V++67jy984QvcdNNN7LHHHp3umiRJ0jJvwJWimblDfTsiPpCZZwNn1/a9HHgUF79ZrkXELsDrMvOoaldjePyztWbbUX7W97eo1pwIbJmZN1fbDwKnUlaYnwU8mJlPAWTm4xFxA3A9MBfYITPnDesDSZIkrYAmTJjApZdeyoc+9CGOPPJI1llnHc477zwmT57c6a5JkiQt8xZnTtFrmndk5m8BIuK4xbiuOu924IcRcQelgvNTwM/qYWVmXghc2HxiNe/obZQAtGEE8D1gA2A3YNuIuDgzz46I9YC1gY2ADTJzXkRMzsxZS+bRJEmSll+ZvQdkbb/99lx99dUd6o0kSdLyazDD53vJzPf2cezioV5XnZeZDwBvA44AbgFWBd7Vrn1ErBURUyNiKmU6hZsyc2Gtyc6UoPQYShB/GnBxRBxJqRA9GzgDODMiXgbcHhEbDvdzSZIkSZIkSTCEStGIWBn4aGb+bx9t9gN+lJmPLE7n1DmZeRmw6QCbTwJuAOYBd1AWVOp1rYiY2Pg8RBlv/1PKMPvdM/OGiBhFWWjp98AFmXnn8DyJJEmSJEmS1NtQhs8/DRwVEf8G3A/8Gbimqi4kIrYEvkKZO9KxPF0gM2+MiNGNeULbtHmk9j4j4m2ZuaC272lgv4iYQRm+L0mSJEmSJC0Rgx4+n5nPUhbYuRlYCdgbuCoiro+IQylzUB6TmQaiXaSvQLRN+wVt9s+sAlJJkiRJkiRpiRhwpWhE7AHclZl/AR7JzK/Vjq0DfBv4PHBJZn5p2HsqSZIkSZIkScNgMJWiBwO/i4i/ARMi4t0RcXxE/Br4LWU1+vWBVSPisCXQV0mSJEmSJElabAOuFM3MN1cL5OwE7At8FJgCnJiZH2u0i4hpwI0R8aPMnDXM/ZUkSZIkSZKkxTKY4fPHVu3/DowGtga+ADwaEacB5wA3AmcCpwHbUBZbkiRJkiRJkqRlRmTmwBpGrAu8G1gLGANMBn6WmSdHxFzgb0ACt2Tmfkumu1JvETEWmDdv3jzGjh3b6e5IkiRJkiSpQ+bPn8+4ceMAxmXm/L7aDmZO0aOBNYEXUqpAHwKeHxGrAQ9l5hbAfcBLq6BKkiRJkiRJkpY5gwlFHwL+AcwFtgLWAP4J3ASMjYjJwDrAGcAJw9pLSZIkSZIkSRomgwlFvwRsB9wJ/JKyyNJvgF2BVYCfUQLTU4Adq+H2kiRJkiRJkrRMGUwo+p/ANZRQ9D7g7cC5wOPAw8BU4INZJin9HvCGYe2pJEmSJEmSJA2DAa8+n5knAkTEeOD6zJwVEe+lBKJHZeZCYGbV/GuZ+dAw91WSJEmSJEmSFtuAQ9GGzHyYEoSSmb+sdp/f1MZAVJIkSZIkSdIyaVChaETsnJm/6uP4aOCTwOqZefjidk4aqBnjZjCGMZ3uhiRJ0rCbntM73QVJkqQVzoBD0YgI4KeURZWIiI2AhUACKwPzKAsvzQE+Nuw9lSRJkiRJkqRhMJg5RTMiHqvtuh1YAASwSmaOiogPAT+uFluSJEmSJEmSpGXOYFafB3im9n5OZo7NzDWAuQCZ+SNgSkRMHa4OSpIkSZIkSdJwGmwoGrX39WrQjIhVI+I04E/Amxa7Z5IkSZIkSZK0BAxmTtExlPAzaB2mPkmZY3SLzLxjmPonSZIkSZIkScNqMKvPN+YTfZpSMTq7fjAznwGOBIiIlTJz4bD0UJIkSZIkSZKG0WCGz/87sD4wpXr1EhEjIuK/IuIm4JTh6Z4kSZIkSZIkDa/BrD7/5/p2GUXf6/izEfEK4GTgh8PROUmSJEmSJEkaboNdaKlujYg4MyLOAlaPiMjMAzPznMycP1wd1IojIlaOiBFN+8ZFc8IuSZKkRcyZM4f111+fWbNmLXLs6KOPZu+99176nZIkSVpODWZO0WZfBp4Cnq3e7xYRXwCOB87NzGeHoX9aRkXEA5T5ZZ9qOjQKGJ+Z41ucdjCwb0S8uvb5+AFwXUR8G1g7My9fUn2WJElaXs2ePZu99967ZSA6c+ZMvvzlL3PjjTcu/Y5JkiQtp4Ycimbmh+rbETEeOB2YDuwDvHlxOqbOi4iJwB+AnTNzVtPhp4C9MnNm0zmTgetaXGsUcBhwSFNg/hBwP6Vq+byI2Dwz/z5sDyFJkrQCmDZtGtOmTePaa6/ttT8zOeSQQzjiiCPYYIMNOtQ7SZKk5c+gh89HxNhW+zPz4cw8GdgU+OjidkydFRFrAT8BJrdp8gywckSMqb+A0UCr4fCHANcAV1TTLmxa7V9Ytb8VOADYvwpWJUmSVDn99NM5/PDDF9l/xhlncNNNN7H++uvzk5/8hIULF3agd5IkScufQVWKVvNBzgZWru3blTKMOqtdI4ExwB3D1Ed1xnnVa/s2xx8Azm9z7L76RkRsA3wYeAXwduCVwHeqz87WwGuB9wG3UD43I9t1KiJGU4LXhjX6exBJkqTl3ZQpUxbZt2DBAj7+8Y/z4he/mPvuu49vfetbfPrTn+ZXv/oVY8aM6UAvJUmSlh+DCkWrFeYfbdr9PeDB2vaLgb8Alyxm39RZB2fmXRFxaquDmbnjIK61B/A84BfAxsAuwBbABGAmcHdmfgSgqjbdtM11AI6hTNEgSZLU1S666CIeffRRLr/8ciZMmMAxxxzDS17yEs455xwOPvjgTndPkiRpmTaUOUWbx+Q8kpkvaWxExN2ZufnidUudlpl3Ne+LiCnAjcACyudgDKVK+OkWlxhJqeLcHPgcMAPYF9g1M68ErqymYjgO2CEiPg9sBUwFfgfs2aZrM4CTa9tr0FSZKkmS1A3uu+8+tttuOyZMmADAqFGj2Hzzzbn77rs73DNJkqRl34BD0Yg4l7K4zhoRcWZjN7BKU9NEK6QqKB3X2I6IO4GDMvOq/s6t5gk9ljJ0nog4EXgLMIsyb+kpwDeBUZm5yEJNtT48CTxZu+7gH0SSJGkFMGnSJB5//PFe++655x523nnnDvVIkiRp+TGYStHrKGHU75r27zZ83dHyIiJeCLyAFivNt2g7qWo3Bzg3IlYHdsvMoyJiFcr8pJcA5wIbR8ROmTlnyfVekiRp+ff617+eQw89lK9+9avstddeXHTRRdx0003ssccene6aJEnSMm/AoWhmfqHV/og4LiKOr+2aUG1/MjNbDavWimE74FHg/hbVmhOBLTPz5mr7QeBUygrzs4AHM/MpgMx8PCJuAK4H5gI7ZOa8Jd57SZKk5dyECRO49NJL+dCHPsSRRx7JOuusw3nnncfkyZM73TVJkqRl3qDnFI2ItwE/zswnql0nUobMB7ANZY7IVYerg1o2ZeaFwIXN+6t5R2+jBKANIygLcm1AqSzeNiIuzsyzI2I9YG1gI2CDzJwXEZMzc9aSfgZJkqTlTWbvmaq23357rr766g71RpIkafk1lIWWTgJ+FRFHU1YPvwK4NjMfiIi/ZOY7hrODWvZFxFrA86vN/wJuysz6glw7Az8GrgZ+BpwG3BYRRwIfA46nhKJnRsRHgN9ExGaZeefSegZJkiRJkiR1j0GFohHxb5RVxxdS5ojcGtgbOCoi1gEmRsTUzLxl2HuqjsjMgaxkNAm4AZgH3EFZUKl+jcsiYmJmPgIQZbz9TynD7HfPzBsiYhRloaXfAxcYiEqSJEmSJGlJGczq898BVgaeBTIzf0oJtoiIfwceA6YDrwIMRbtIZt4YEaMb84S2afNI7X1GxNsyc0Ft39PAfhExA7h9yfZYkiRJkiRJ3WzEINp+C3h7dc6IiNgpIr4ZEQ8APwe2AH4JvG74u6llXV+BaJv2C9rsn+kCXZIkSZIkSVqSBrP6/CUAETEaWAlYhVIRekJm3lYd2wrYISJGZOazS6C/kiRJkiRJkrRYhrLQ0huBuZl5GXBZ07FbgY0MRCVJkiRJkiQtqwYdimbmDX0cexJ4crF6JEmSJEmSJElL0GDmFJUkSZIkSZKk5V5kZqf7IA1ZRIwF5s2bN4+xY8d2ujuSJEmSJEnqkPnz5zNu3DiAcZk5v6+2VopKkiRJkiRJ6iqGopIkSZIkSZK6iqGoJEmSJEmSpK5iKCpJkiRJkiSpqxiKSpIkSZIkSeoqhqKSJEmSJEmSusqoTndAGg4zxs1gDGM63Q1JkiRJbUzP6Z3ugiRJz7FSVJIkSZIkSVJXMRSVJEmSJEmS1FUMRSVJkiRJkiR1FUNRSZIkSZIkSV3FUFSSJEmSJElSVzEUlSRJkiRJktRVDEUlSZIkSZIkdRVDUUmSJEnSUvF///d/TJkyhVGjRrHddttx2223PXdszpw5rL/++syaNatzHZQkdQ1DUS01EbFyRIxo2jcuIqJTfZIkSZK0dPz1r3/loIMO4oQTTuD+++9nvfXW4z3veQ8As2fPZq+99jIQlSQtNYaiGpKIeCAi/hYRdza9ZkXEw21OOxi4oikY/QEwIyJeEhG7LPGOS5IkSeqI2267jeOPP559992X5z//+bzvfe/jD3/4AwDTpk1j2rRpHe6hJKmbjOp0B9Q5EfFG4BTgRcD1wIGZeVt1bCLwB2DnzJzV4vSngL0yc2bTNScD17W41yjgMOCQzHy2dugh4H5KQH9eRGyemX9fzEeTJEmStIzZa6+9em3/+c9/ZsMNNwTg9NNPZ8qUKRxxxBEd6JkkqRtZKdqlImID4CzgaOAFwD3A16tjawE/ASb3cYlngJUjYkz9BYwGWg2HPwS4hlIpemZEbFrtX1i1vxU4ANi/ClYlSZIkraCeeuopTjrpJN7//vcDMGXKlA73SJLUbawU7V7/DnwsM88HiIivAJdWx86rXtv3cf4DwPltjt1X34iIbYAPA68A3g68EvhOROwKbA28FngfcAtwBzCy3U0jYjQleG1Yo48+SpIkSVoGffzjH2f11Vfn4IMP7nRXJEldylC0S2XmT5p2bQzcWb0/ODPviohT+zh/x0Hcbg/gecAvqvvsAmwBTABmAndn5kcAqmrTTdtcB+AYYPog7i1JkiRpGfLzn/+cr371q1x77bWstNJKne6OJKlLGYqKiFiZUsl5CkBm3tWm3RTgRmABZdj7GODp6tVsJKWKc3Pgc8AMYF9g18y8ErgyIsYCxwE7RMTnga2AqcDvgD3bdHcGcHJtew2aKlMlSZIkLZvuuusu9ttvP77yla+w6aZ91UJIkrRkGYoK4FOUoPP0vhpVYem4xnZE3AkclJlX9XeDap7QYylD54mIE4G3ALMoc5eeAnwTGJWZiyzUVOvDk8CTtev2d2tJkiRJy4DHH3+cvfbai3322Yc3vvGNLFiwAIDVVlvNv9dLkpY6Q9EuFxG7Ae8Fts/MhYM474WUBZraBpi1tpOqdnOAcyNidWC3zDwqIlahzE96CXAusHFE7JSZcwb/NJIkSZKWVZdddhm33XYbt912G2ecccZz+++++24mT57cuY5JkrqSoWgXq4bDfxt4X2beOsjTtwMeBe5v8VvdicCWmXlztf0gcCplhflZwIOZ+RRAZj4eETcA1wNzgR0yc97gn0aSJEnSsmyfffYhM/ts099xSZKGy4hOd0CdUVVo/gT4IfB/EbF69RrQuJXMvDAz12p+AdsCT1EC0IYRwPeAx4DdgC9GxIFVP9YD1gY2At6ZmfOqofaSJEmSJEnSEmEo2r1eC/w78F/AI7XXeoO9UESsFRFTI2IqcBhwU9NQ/J2B2ygrx48CTgMujogjKRWiZwNnAGdGxMuA2yNiw6E+mCRJkiRJktQXh893qcz8IdBnVWhmDnS280nADcA84A7Kgkr161wWERMz8xHg/7d39+Fa1XXe999f3Ag2sLcPlDZKbBGzwMerFC97mNRbJaULqom8o+mWOwOptHyoNJkDO+4C55YpJmdEcw6jfIhML3PyITI1tbzJJ7QhNl4ikILOXIKyN1tRQL/3H+vczOnJ3jzuzclmvV/HsQ72+q3fuc7v4ljHAj78futHZTTqXRTT7E/NzCciooFioaVHgVsyc/E2XI4kSZIkSZK01QxFtcMyc35E9Ot4T2gXfdZU/ZwR8ZnMbK9q2wCMj4jpwKKerViSJEmSJEllZiiqbrG5QLSL/u1dtC/onookSZIkSZKkzvlOUUmSJEmSJEmlYigqSZIkSZIkqVQMRSVJkiRJkiSViqGoJEmSJEmSpFKJzKx3DdJ2i4hGoLW1tZXGxsZ6lyNJkiRJkqQ6aWtro6mpCaApM9s219eRopIkSZIkSZJKxVBUkiRJkiRJUqkYikqSJEmSJEkqFUNRSZIkSZIkSaViKCpJkiRJkiSpVBrqXYDUHaY3Tac//etdhiRJkiRts6k5td4lSFLpOFJUkiRJkiRJUqkYikqSJEmSJEkqFUNRSZIkSZIkSaViKCpJkiRJkiSpVAxFJUmSJEmSJJWKoagkSZIkSZKkUjEUlSRJkiRJklQqhqKSJEmSJO3iVq1axcMPP8zKlSvrXYok7RYMRbXTRMSeEdGnpq0pIqJeNUmSJEnSruL2229n6NChNDQ0MHLkSFpaWgCYM2cOw4YN4ytf+Qrvec97mDNnTp0rlaTez1BU2yUiXoiI5yJicc22LCJWd/GxicDvaoLR24DpEXFERJzU44VLkiRJ0i7o2WefZcKECVx++eWsWLGCIUOGcPbZZ7N69WrOPfdcHnroIebPn88111zDt771rXqXK0m9nqGotigifh0RZ9U0rwNOz8xh1Rvwscqx2nM0AOcBUzPzrapDLwErKO7FORFxQE9cgyRJkiTtylpaWpg2bRrjxo1j//33Z/LkyTz22GOsWbOGmTNncvjhhwNw1FFH8corr9S5Wknq/RrqXYB2bRExHjgNqJ2f8SawZ0T0r2nvB3Q2HX4S8DDFSNHrgBmZuRBYX+m/EPgC8PmIuCUzl3XfVUiSJEnSrm306NFv23/66acZNmwYgwcPZvz48QCsX7+eGTNm8KlPfaoeJUrSbsVQVF2KiH2BfwSe7uTwC8DNXXx0ec15jgUuAj4EfBb4MHBTRJwMfIAidJ0M/Bl4BthjMzX1owheOwzcmmuRJEmSpN5i3bp1zJgxg/PPP39j21NPPcWJJ57InnvuyaJFi+pYnSTtHgxFtTn/SPHOz71qD2TmR7bhPKOAdwG/BQ4DTgKOAvYFFgBLM/ObAJWRp8M3c65LgKnb8N2SJEmS1KtMmTKFAQMGMHHixI1tRx55JPfeey8XXXQREyZM4LbbbqtjhZLU+0Vm1rsG7YIi4kTgJ8DhwA+B3wEPAvOBdopp7/2BDZWt1h4UoziPBFZSvGd0HHByZn6x8h2NwGXAccDjwDHACOCPmXl6F3V1NlJ0+cVcTH9qZ/JLkiRJ0q5vav7XuI977rmHT3/608ybN4/hwzcdL/L8888zZMgQVq1axT777LMzy5SkXV5bWxtNTU0ATZnZtrm+jhTVJiqjNa8BJmdmW0TxitDMXAI0VfVbDEzIzIe24pzNwKUUU+eJiCuATwPLgGbgBxQhbENmPtLVeTLzDeCNqvNu07VJkiRJ0q5qyZIljB8/nlmzZm0MRO+77z7uvvturrjiCgAaGop/xvfp47rJkrQjDEXVmb8HHs3MO7vqEBEHAQcCXQaYVX0HV/qtAm6IiAHAKZn5jYjYi+L9pHcDNwCHRcRHM3NVN1yHJEmSJPUKa9euZfTo0YwdO5YxY8bQ3t4OwGGHHcbYsWM59NBD+fjHP86UKVM49dRTO0ZCSZK2k/+1pM58DhgTEasjYnVl/6qIuKqqz0jgVWBFRKys2TIijqrq+yIwk+J9oJcC4zJzHUBmrgWeoJg+fwBwgoGoJEmSpLKZO3cuLS0tXHvttQwcOHDjtn79en7xi18wc+ZMRowYwWuvvcb1119f73IlqddzpKg68xHefm/MAOYBszsaMvNW4NbaD0bEUKAFWFjV3Af4OXAIcApwXETcmZmzI2II8E7gvcAhmdkaEc2Zuaxbr0iSJEmSdmFjx46lqzU/mpubWbhwYafHJEnbx1BUm8jM5dX7EdEOrMzMlZ31j4hBwP6V3S8BT2bm+qouJwK/Av4A/Aa4EmiJiAuAbwPTKELR6yLim8DvI+LwzFzcjZclSZIkSZIkAYai2gqZedYWugymmALfCjxDMUW++vNzI2K/zFwDEMXqSHcB+wGnZuYTEdFAsdDSo8AtBqKSJEmSJEnqKYai2mGZOT8i+nW8J7SLPmuqfs6I+Exmtle1bQDGR8R0YFHPVixJkiRJkqQyMxRVt9hcINpF//Yu2hd0T0WSJEmSJElS51x9XpIkSZIkSVKpGIpKkiRJkiRJKhVDUUmSJEmSJEmlYigqSZIkSZIkqVQiM+tdg7TdIqIRaG1tbaWxsbHe5UiSJEmSJKlO2traaGpqAmjKzLbN9XWkqCRJkiRJkqRSMRSVJEmSJEmSVCqGopIkSZIkSZJKxVBUkiRJkiRJUqkYikqSJEmSJEkqFUNRSZIkSZIkSaXSUO8CpO4wvWk6/elf7zIkSZIkqdebmlPrXYIk9ThHikqSJEmSJEkqFUNRSZIkSZIkSaViKCpJkiRJkiSpVAxFJUmSJEmSJJWKoagkSZIkSZKkUjEUlSRJkiRJklQqhqKSJEmSJEmSSsVQVJIkSZIkSVKpGIpqp4mIPSOiT01bU0REvWqSJEmSJG3q9ttvZ+jQoTQ0NDBy5EhaWlo26TNq1Chmz56984uTpG5gKKrtEhEvRMRzEbG4ZlsWEau7+NhE4Hc1wehtwPSIOCIiTurxwiVJkiRJm/Xss88yYcIELr/8clasWMGQIUM4++yz39bnxhtvZO7cuXWqUJJ2nKGoOhURV0ZEVm2La7qsA07PzGHVG/CxyrHa8zUA5wFTM/OtqkMvASso7sU5EXFAj1yQJEmSJGmrtLS0MG3aNMaNG8f+++/P5MmTeeyxxzYef/nll7nwwgs57LDD6lilJO2YhnoXoF3WB4AzgIcr+2/WHH8T2DMi+te09wM6mw4/qXKu30XEdcCMzFwIrK/0Xwh8Afh8RNySmcu65SokSZIkSdtk9OjRb9t/+umnGTZs2Mb9Cy+8kE9+8pOsXbt2Z5cmSd3GUFSbqIzqPBx4MDPbu+j2AnBzF8eW15zvWOAi4EPAZ4EPAzdFxMkU4etpwGTgz8AzwB6bqa0fRfDaYeCWrkeSJEmStH3WrVvHjBkzOP/88wG4//77uffee1mwYAHnnXdenauTpO1nKKrOHEExevPJiDgQeACYmJnPdXTIzI9sw/lGAe8CfgscBpwEHAXsCywAlmbmNwEqI0+Hb+ZclwBTt+G7JUmSJEnbacqUKQwYMICJEyfy+uuvM2nSJGbNmkVjY2O9S5OkHWIoqs4Mpxi1eS6wEvghcE1EfAWYD7RTTHvvD2yobLX2oBjFeSTwj8B0YBxwcmY+ADwQEY3AZcAJEfFPwDHACOCPwOld1DYd+H7V/kBqRqZKkiRJknbcPffcw9VXX828efPo27cvl112GcceeyxnnHFGvUuTpB1mKKpNZOaNwI0d+xHxVWAJsDIzm6raFwMTMvOhLZ0zIpqBSymmzhMRVwCfBpYBzcAPgJ8ADZn5yGZqewN4o+q8W39hkiRJkqStsmTJEsaPH8+sWbMYPryYzHfTTTfx0ksvsffeewPw2muvcfPNN/PII49w1VVX1bFaSdp2hqLaGqspVod/N9AGEBEHAQcCXQaYHSJicKXfKuCGiBgAnJKZ34iIvSjeT3o3cANwWER8NDNX9cSFSJIkSZI2b+3atYwePZqxY8cyZswY2tuLpSYefPBB3nzzv9bgveiiizj++OM566yz6lSpJG0/Q1FtIiK+D8zLzI6FlI4F3gKer+o2EngVWNHJaM39gKMz86nK/ovATIoV5pcBL2bmOoDMXBsRTwCPA68AJ2Rma3dfkyRJkiRp68ydO5eWlhZaWlq49tprN7YvXbqU5ubmjfsDBgxg0KBBDBo0qA5VStKOMRRVZ54EvhcR/0Fxj1wJzM7M1zo6ZOatwK21H4yIoUALRQDaoQ/wc+AQ4BTguIi4MzNnR8QQ4J3Ae4FDMrM1Ipozc1mPXJkkSZIkabPGjh1LZm6x3+zZs3u+GEnqIYai2kRm/jQi3g/cDqwBbgO+3VX/iBgE7F/Z/RLwZGaur+pyIvAr4A/AbyhC1paIuKBy3mkUoeh1EfFN4PcRcXhmLu7eK5MkSZIkSZIMRdWFzLwEuGQruw8GngBagWcoFlSqPtfciNgvM9cARDHf/i6KafanZuYTEdFAsdDSo8AtBqKSJEmSJEnqKYai2mGZOT8i+nW8J7SLPmuqfs6I+Exmtle1bQDGR8R0YFHPVixJkiRJkqQyMxRVt9hcINpF//Yu2hd0T0WSJEmSJElS5/rUuwBJkiRJkiRJ2pkMRSVJkiRJkiSViqGoJEmSJEmSpFIxFJUkSZIkSZJUKpGZ9a5B2m4R0Qi0tra20tjYWO9yJEmSJEmSVCdtbW00NTUBNGVm2+b6OlJUkiRJkiRJUqkYikqSJEmSJEkqFUNRSZIkSZIkSaViKCpJkiRJkiSpVAxFJUmSJEmSJJWKoagkSZIkSZKkUmmodwFSd5jeNJ3+9K93GZIkSZLU603NqfUuQZJ6nCNFJUmSJEmSJJWKoagkSZIkSZKkUjEUlSRJkiRJklQqhqKSJEmSJEmSSsVQVJIkSZIkSVKpGIpKkiRJkiRJKhVDUUmSJEmSJEmlYigqSZIkSZIkqVQMRbXTRMSeEdGnpq0pIqJeNUmSJEmSNnX77bczdOhQGhoaGDlyJC0tLZv0GTVqFLNnz975xUlSNzAU1XaJiBci4rmIWFyzLYuI1V18bCLwu5pg9DZgekQcEREn9XjhkiRJkqTNevbZZ5kwYQKXX345K1asYMiQIZx99tlv63PjjTcyd+7cOlUoSTvOUFSdiogxEbEkIjZExB8j4v01XdYBp2fmsOoN+FjlWO35GoDzgKmZ+VbVoZeAFRT34pyIOKBHLkiSJEmStFVaWlqYNm0a48aNY//992fy5Mk89thjG4+//PLLXHjhhRx22GF1rFKSdkxDvQvQriciDgF+DJwDPABcCfwr8KGqbm8Ce0ZE/5qP9wM6mw4/CXiYYqTodcCMzFwIrK/0Xwh8Afh8RNySmcu674okSZIkSVtr9OjRb9t/+umnGTZs2Mb9Cy+8kE9+8pOsXbt2Z5cmSd3GUFSdeT/w7cy8GSAiZgG/runzAnBzF59fXr0TEccCF1GEqp8FPgzcFBEnAx8ATgMmA38GngH26KqwiOhHEbx2GLh1lyRJkiRJ2lbr1q1jxowZnH/++QDcf//93HvvvSxYsIDzzjuvztVJ0vYzFNUmMvOOmqbDgMU1fT6yDaccBbwL+G3lXCcBRwH7AguApZn5TYDKyNPhmznXJcDUbfhuSZIkSdJ2mjJlCgMGDGDixIm8/vrrTJo0iVmzZtHY2Fjv0iRphxiKarMiYk+KUZ4/iIihwHygnWLae39gQ2WrtQfFKM4jgX8EpgPjgJMz8wHggYhoBC4DToiIfwKOAUYAfwRO76Kk6cD3q/YHUjMyVZIkSZK04+655x6uvvpq5s2bR9++fbnssss49thjOeOMM+pdmiTtMENRbcl3KULQH2XmeqCp40BELAYmZOZDWzpJRDQDl1JMnScirgA+DSwDmoEfAD8BGjLzka7Ok5lvAG9UnXdbr0eSJEmStAVLlixh/PjxzJo1i+HDi8l8N910Ey+99BJ77703AK+99ho333wzjzzyCFdddVUdq5WkbWcoqi5FxCkUiy0dXwlEq48dBBwIdBlgVvUdXOm3CrghIgYAp2TmNyJiL4r3k94N3AAcFhEfzcxV3Xs1kiRJkqStsXbtWkaPHs3YsWMZM2YM7e3tADz44IO8+eabG/tddNFFHH/88Zx11ll1qlSStp+hqDpVmSp/IzC5skp8rZHAq8CKTkZr7gccnZlPVfZfBGZSrDC/DHgxM9cBZObaiHgCeBx4BTghM1u792okSZIkSVtr7ty5tLS00NLSwrXXXruxfenSpTQ3N2/cHzBgAIMGDWLQoEF1qFKSdkxkZr1r0C6mMnrzceD3wAVVh17NLdwwlTC1BRjQMbq08l7SwcAhFAssHQfcmZmzI2II8CuKd4kekpnLIqI5M5dtZa2NQOvFXEx/+m/LZUqSJEmSOjE1XdtWUu/U1tZGU1MTQFNmtm2ub5+dU5J6mdOA9wNfAtZUbUM66xwRgyJiRESMAM4DnqyZbn8iRVB6CcXo5CuBOyPiAorwdTZwLXBdRHwQWBQRw3riwiRJkiRJkiSnz2sTmflLYFtWMBoMPAG0As9QLKhUfb65EbFfZq4BiGK+/V0U0+xPzcwnIqKBYqGlR4FbMnPxDl+IJEmSJEmS1AlDUe2wzJwfEf063hPaRZ81VT9nRHwmM9ur2jYA4yNiOrCoZyuWJEmSJElSmRmKqltsLhDton97F+0LuqciSZIkSZIkqXO+U1SSJEmSJElSqRiKSpIkSZIkSSoVQ1FJkiRJkiRJpWIoKkmSJEmSJKlUIjPrXYO03SKiEWhtbW2lsbGx3uVIkiRJkiSpTtra2mhqagJoysy2zfV1pKgkSZIkSZKkUjEUlSRJkiRJklQqhqKSJEmSJEmSSsVQVJIkSZIkSVKpGIpKkiRJkiRJKhVDUUmSJEmSJEml0lDvAqTuML1pOv3pX+8yJEmSJEndbGpOrXcJknZDjhSVJEmSJEmSVCqGopIkSZIkSZJKxVBUkiRJkiRJUqkYikqSJEmSJEkqFUNRSZIkSZIkSaViKCpJkiRJkiSpVAxFJUmSJEmSJJWKoajeJiKOiIiRW9GvsernPSJir8rPAyIiuvhM/07a9t6BciVJkiRJJXD77bczdOhQGhoaGDlyJC0tLQCce+65RMTGbdiwYXWuVFJvYSiqWqcCsyNiS/fG/Ig4u/LzYGBlJeBcAwzo4jPfjYgbatqeiIhzIuIjEfGB7a5akiRJkrRbevbZZ5kwYQKXX345K1asYMiQIZx9dvHP0ccff5w777yTV155hVdeeYX58+fXuVpJvUVDvQvQLudfgVHAAcALUIwEBfpm5uuV/Y8CBwJ3RUQDsA54BXijco5Xa09aCUzHAyfWHHoJWEERpF4fEe/PzLXdfE2SJEmSpF6qpaWFadOmMW7cOAAmT57MqFGj2LBhAwsWLOCjH/0oAwZ0NTZHkjrnSNGSi4gXI+LNiNgQERuAVRTB5XNVbeuBtVXT378BzAH+G/A6sIwiJH2lcvy1yjnHVX3VpcA1wPMRcUNEHFhpXw8EcD/wNeDCiPBPM0mSJEkSAKNHj+acc87ZuP/0008zbNgw/v3f/53M5Oijj2avvfZi1KhRPPfcc3WsVFJvYiiqV4HTM7NhM1sfYM/MfD0i/jtwBvC7zLwjMxuA9wB/AfYGyMz+wC+AVoCI+ARwOvB94KvAEGBERFwADKUISx8FzgT6AZu8e1SSJEmSpHXr1jFjxgy+/OUvs3DhQkaMGMHPfvYzFi5cSN++fZk0aVK9S5TUSzh9XmuBvlvqlJnrKyNFZwHPAETEaRSB5h7Au4GnK+3LgHcCP618fCxwEPAI0AwcAXy+8t1PA7/IzKsqnx1Y6bOyszoioh9FcNph4NZdpiRJkiSpt5syZQoDBgxg4sSJ9O3bl/Hjx2889s///M8MHTqUtrY2GhsbN3MWSTIUVWFrRwyPpJhe/0xl/53APIrp9A8Aw4G1mdlc87mvA2cDlwB7ZOYzwNSI2A84Bjg9Io6o/DwM+J/AxC5quASYupX1SpIkSZJ2E/fccw9XX3018+bNo2/fTcf27L333rz11lu8+OKLhqKStsjp8+oD5NZ0zMwHKKbOdxhAschSP4p3g3b1uTXAB4BPA/8AEBE3A7+nWLl+MHAXcAHwoczsKhAFmA40VW0HbU3tkiRJkqTea8mSJYwfP55Zs2YxfPhwAC644AJuvvnmjX0effRR+vTpw+DBg+tVpqRexJGi2g94bWs7V94r2rHbh+JdoWMp3gO6HCAiVgJ7Urx39H9ExAeB+4D/BfxbRLQBn8/MdRFxKHBn5fhvgTciYlTHSvedfP8b/Ncq91TVIkmSJEnaDa1du5bRo0czduxYxowZQ3t7OwBHHXUUl156KQcccAAbNmzg3HPP5ayzzuId73hHnSuW1BsYipZYROwFDKISZm6ryntAr4qIb1EsnnQBxfT5QRFxJvCZSte/AP8P0FL5+YXMXFc5xzMR0Qd4DFgEfLbjmCRJkiRJc+fOpaWlhZaWFq699tqN7UuXLmXRokWMGTOGgQMH8slPfpJp06bVsVJJvYmhaLmdRDFKdMn2niAi+gJnARdWtR0OfBxYXWlqB/6N4n2h/wMYGRH/kplzI+JIilGl7wSOrYwebc7MZdtbkyRJkiRp9zF27FgyO3/r2/Tp05k+ffpOrkjS7sB3ipZUFPPOvwn8W2Z2+T7QLuwB9ImIdwDXU4z8vAvomMs+jGI1+qsq+18A5gNfBl4Hvgc8FRHfpZg2fwnwB+BHEXEq8OeI8K3YkiRJkiRJ6hGOFC2vDwPHA1/djs/2r2w/AQZSLKAE0LH8368z85dV/a8DftLxntCI6Ac8AvwHMDIzn42I24FfAnOBGZnZth11SZIkSZIkSVtkKFpSmflQRBycmS9sx8e/RrHq/L9Wv/+zEmRusvJRZSTq+qr9NyLiw5VV6Tva2iPiFOAI4N+3oyZJkiRJkiRpqxiKlth2BqJk5svd8N1rOmlL4E87em5JkiRJkiRpc3ynqCRJkiRJkqRSMRSVJEmSJEmSVCqGopIkSZIkSZJKxVBUkiRJkiRJUqkYikqSJEmSJEkqlSgW/JZ6p4hoBFpbW1tpbGysdzmSJEmSJEmqk7a2NpqamgCaMrNtc30dKSpJkiRJkiSpVAxFJUmSJEmSJJWKoagkSZIkSZKkUjEUlSRJkiRJklQqhqKSJEmSJEmSSqWh3gVI3WF603T607/eZUiSJEmSdmNTc2q9S5DUTRwpKkmSJEmSJKlUDEUlSZIkSZIklYqhqCRJkiRJkqRSMRSVJEmSJEmSVCqGopIkSZIkSZJKxVBUkiRJkiRJUqkYikqSJEmSJEkqFUNRSZIkSZIkSaViKKqdJiL2jIg+NW1NERH1qkmSJEmSpG11++23M3ToUBoaGhg5ciQtLS1vO37xxRfziU98ok7VSdoahqLaLhHxQkQ8FxGLa7ZlEbG6i49NBH5XE4zeBkyPiCMi4qQeL1ySJEmSpB3w7LPPMmHCBC6//HJWrFjBkCFDOPvsszceX7BgAVdddRUzZ86sX5GStshQVJ2KiL+rhJ7tEfHbiGiu6bIOOD0zh1VvwMcqx2rP1wCcB0zNzLeqDr0ErKC4F+dExAE9cT2SJEmSJHWHlpYWpk2bxrhx49h///2ZPHkyjz32GACZyaRJk/j617/OIYccUudKJW2Ooag2ERGHAN8DxgLDgb8As2u6vQnsGRH9qzegH9DZdPhJwMMUI0Wvi4jhlfb1lf4LgS8An+8kgJUkSZIkaZcwevRozjnnnI37Tz/9NMOGDQPg2muv5cknn+Tggw/mjjvuYP369fUqU9IWNNS7AO2SjgHmZeYTABHxY+Dmmj4vdNLWYXn1TkQcC1wEfAj4LPBh4KaIOBn4AHAaMBn4M/AMsEdXhUVEP4rgtcPArbskSZIkSZK617p165gxYwbnn38+7e3tTJkyhUMPPZTly5dz/fXX873vfY/777+f/v3717tUSTUMRdWZhcBJEXEMsAT4CnBPdYfM/Mg2nG8U8C7gt8BhwEnAUcC+wAJgaWZ+E6Ay2nR4F+cBuASYug3fLUmSJElSj5gyZQoDBgxg4sSJ/OxnP+PVV1/lvvvuY9999+WSSy7hiCOO4Kc//SkTJ06sd6mSahiKahOZuTAibgGeqDQtBUZGxFBgPtBOMe29P7ChstXag2IU55HAPwLTgXHAyZn5APBARDQClwEnRMQ/UYxQHQH8ETi9i/KmA9+v2h9IzchUSZIkSZJ62j333MPVV1/NvHnz6Nu3L8uXL2fkyJHsu+++ADQ0NHDkkUeydOnSOlcqqTOGotpERBwPfAIYSTFq9BLgLuC4zGyq6rcYmJCZD23FOZuBSymmzhMRVwCfBpYBzcAPgJ8ADZn5SFfnycw3gDeqzrtN1yZJkiRJ0o5asmQJ48ePZ9asWQwfXkx2HDx4MGvXrn1bv7/85S+ceOKJ9ShR0ha40JI681lgTmY+kpntwBRgKMWUdwAi4iDgQKDLALOq7+BKvz7ADRHxAHBpZg4FzgD+Cri78j0/joj9uvl6JEmSJEnqFmvXrmX06NGMHTuWMWPG0N7eTnt7O6effjotLS1cffXVLF++nB/+8Ic8+eSTjBo1qt4lS+qEI0XVmQZgn6r9gRTBZfUCSCOBV4EVnYzW3A84OjOfquy/CMykGHW6DHgxM9cBZObaiHgCeBx4BTghM1u782IkSZIkSeouc+fOpaWlhZaWFq699tqN7UuXLuXXv/41F154IRdccAEHHHAAc+bMobm5uX7FSuqSoag68wfguog4H/hP4OzKr3/q6JCZtwK31n6w8t7RFooAtEMf4OfAIcApwHERcWdmzo6IIcA7gfcCh2Rma0Q0Z+ayHrkySZIkSZJ2wNixY8nMTo81Nzfzhz/8YSdXJGl7GIqqMz+nWCX+68C7KVaI/1Rmru+sc0QMAvav7H4JeLKm74nAryjC1t8AVwItEXEB8G1gGkUoel1EfBP4fUQcnpmLu/vCJEmSJEmSJENRbSKL//L6TmXbGoMpVqpvBZ6hWFCp+nxzI2K/zFwDEMV8+7soptmfmplPREQDxUJLjwK3GIhKkiRJkiSppxiKaodl5vyI6NfxntAu+qyp+jkj4jOVRZw62jYA4yNiOrCoZyuWJEmSJElSmRmKqltsLhDton97F+0LuqciSZIkSZIkqXN96l2AJEmSJEmSJO1MhqKSJEmSJEmSSsVQVJIkSZIkSVKpGIpKkiRJkiRJKpXIzHrXIG23iGgEWltbW2lsbKx3OZIkSZIkSaqTtrY2mpqaAJoys21zfR0pKkmSJEmSJKlUDEUlSZIkSZIklYqhqCRJkiRJkqRSMRSVJEmSJEmSVCqGopIkSZIkSZJKxVBUkiRJkiRJUqk01LsAqTtMb5pOf/rXuwxJkiRJkqRd3tScWu8S6s6RopIkSZIkSZJKxVBUkiRJkiRJUqkYikqSJEmSJEkqFUNRSZIkSZIkSaViKCpJkiRJkiSpVAxFJUmSJEmSJJWKoagkSZIkSZKkUjEUlSRJkiRJkkpq1apVPPzww6xcubLepexUhqLaaSJiz4joU9PWFBFRr5okSZIkSZLKas6cOQwbNoyvfOUrvOc972HOnDkbj61atYqDDz6YZcuW1a/AHmQoqu0SES9ExHMRsbhmWxYRq7v42ETgdzXB6G3A9Ig4IiJO6vHCJUmSJEmSxOrVqzn33HN56KGHmD9/Ptdccw3f+ta3AFi5ciWjR4/ebQNRMBTVFkTE5RHxq04OrQNOz8xh1Rvwscqx2vM0AOcBUzPzrapDLwErKO7FORFxQLdfhCRJkiRJkt5mzZo1zJw5k8MPPxyAo446ildeeQWAM888kzPPPLOe5fU4Q1F1KSIOB74MfL2Tw28Ce0ZE/+oN6Ad0Nh1+EvAwxUjR6yJieKV9faX/QuALwOcjorl7r0SSJEmSJEnVBg8ezPjx4wFYv349M2bM4FOf+hQAP/rRj/ja175Wz/J6XEO9C9CuqfKez2uAmZn5bCddXgBu7uLjy2vOdSxwEfAh4LPAh4GbIuJk4APAacBk4M/AM8Aem6mrH0Xw2mHg1lyPJEmSJEmSNvXUU09x4oknsueee7Jo0SIAhg4dWueqep4jRdWVLwFHA0sjYnRE9K0+mJkfqZ06X7UdU3OuUcC7gN8CN1bOPRzYD1gA/Dgz35+Zfwt8B2jaTF2XAK1V2/LN9JUkSZIkSdJmHHnkkdx7772MGDGCCRMm1LucnSYys941aBcTEQOAJRSjQW8FTgT2Ar4I/H9AO8W09/7AhspWaw+KUZxHAisp3jM6Djg5M79Y+Z5G4DLgOOBx4BhgBPDHzDy9i9o6Gym6/GIupj/9t/uaJUmSJEmSymJqTt2k7fnnn2fIkCGsWrWKffbZB4CIYOnSpTQ3N+/kCrdPW1sbTU1NAE2Z2ba5vk6fV2c+BfwVcFJmvhwR04F/Bz6cmRtHcUbEYmBCZj60pRNW3hN6KcXUeSLiCuDTwDKgGfgB8BOgITMf6eo8mfkG8EbVebfx0iRJkiRJknTfffdx9913c8UVVwDQ0FDEhH36lGNiuaGoOnMQxWjNlwEyc0NE/Ak4uKNDRBwEHAh0GWBW9R1c6bcKuKEyEvWUzPxGROxFMSL1buAG4LCI+Ghmrurui5IkSZIkSVLhfe97H2PHjuXQQw/l4x//OFOmTOHUU0/tGGm52ytH9Ktt9TzFdPlqQ4C/VO2PBF4FVkTEypotI+Koqr4vAjMp3gd6KTAuM9cBZOZa4AmK6fMHACcYiEqSJEmSJPWsv/7rv+YXv/gFM2fOZMSIEbz22mtcf/319S5rp3GkqDpzJ3BlRJwD3EExnf5o4NcdHTLzVor3jb5NRAwFWoCFVc19gJ8DhwCnAMdFxJ2ZOTsihgDvBN4LHJKZrRHRnJnLeuLCJEmSJEmSVDjttNNYuHBhl8d357WIHCmqTVSmzY8C/g74X8DXgTO7CiojYlBEjIiIEcB5wJOZub6qy4kUQeklFEH8lcCdEXEBxQjR2cC1wHUR8UFgUUQM64FLkyRJkiRJkhwpqs5l5jzgQ1vZfTDFFPhW4BmKKfLV55obEftl5hqAKFZHugvYDzg1M5+IiAaKhZYeBW7JzMXdcyWSJEmSJEnS2xmKaodl5vyI6NfxntAu+qyp+jkj4jOZ2V7VtgEYX1npflHPVixJkiRJkqQyMxRVt9hcINpF//Yu2hd0T0WSJEmSJElS53ynqCRJkiRJkqRSMRSVJEmSJEmSVCqGopIkSZIkSZJKxVBUkiRJkiRJUqlEZta7Bmm7RUQj0Nra2kpjY2O9y5EkSZIkSVKdtLW10dTUBNCUmW2b6+tIUUmSJEmSJEmlYigqSZIkSZIkqVQMRSVJkiRJkiSViqGoJEmSJEmSpFIxFJUkSZIkSZJUKoaikiRJkiRJkkrFUFSSJEmSJElSqRiKSpIkSZIkSSoVQ1FJkiRJkiRJpWIoKkmSJEmSJKlUDEUlSZIkSZIklYqhqCRJkiRJkqRSMRSVJEmSJEmSVCqGopIkSZIkSZJKxVBUkiRJkiRJUqkYikqSJEmSJEkqFUNRSZIkSZIkSaViKCpJkiRJkiSpVAxFJUmSJEmSJJWKoagkSZIkSZKkUjEUlSRJkiRJklQqhqKSJEmSJEmSSsVQVJIkSZIkSVKpGIpKkiRJkiRJKhVDUUmSJEmSJEml0lDvAqTu0NbWVu8SJEmSJEmSVEfbkg9FZvZgKVLPiohmYGm965AkSZIkSdIu46DMXLG5Do4UVW/3cuXXg4A19SxE2gEDgeV4H6v3817W7sJ7WbsD72PtLryXtTvwPt65BgIvbKmToah2F2sy0zn06pUiouNH72P1at7L2l14L2t34H2s3YX3snYH3sc73Vb9HrvQkiRJkiRJkqRSMRSVJEmSJEmSVCqGourt3gC+U/lV6q28j7W78F7W7sJ7WbsD72PtLryXtTvwPt4Fufq8JEmSJEmSpFJxpKgkSZIkSZKkUjEUlSRJkiRJklQqhqKSJEmSJEmSSsVQVJIkSZIkSVKpGIpKUh1FxJURkVXb4nrXJEllExH7RcTSiGiuavP5LEk7WUSMiYglEbEhIv4YEe+vtPtMVq9T+fvFCRExqN61qHOGouq1IuLwiHg0Il6JiCsiIupdk7QdPgCcAexT2Y6pbznS1usiSPLZrF6l8g+VO4DmmkM+n9WrbCZM8rmsXiEiDgF+DFwMHAj8BfjXymGfyepVIuJMYDHwL8BzlX2fybsYQ1H1ShHRD/gV8DjwQWA4cFY9a5K2VUQ0AIcDD2bm6sq2pt51SVujsyDJZ7N6qTmVbSOfz+ptugqTfC6rl3k/8O3MvDkz/xOYBXzQZ7J6m4jYG7gS+EhmHgNMAv7BZ/Kux1BUvdXHgSbggsx8Fvg28MX6liRtsyOAAJ6MiLUR8euIeE+9i5K20iZBEj6b1TtNzMx/qmnz+azeptMwCZ/L6kUy847MvLqq6TCKkXY+k9XbDAS+npkLKvtPUYxw9pm8izEUVW91FDAvM1+r7P+J4n9ZpN5kOPBn4P+s/LweuKauFUlbr7MgyWezep3MXNJJs89n9SqbCZN8LqtXiog9gYuAq/CZrF4mM5/PzBsBIqIvxb38P/GZvMtpqHcB0nZqBJZ27GRmRsSbEbFPZr5Sx7qkrVb5g/LGjv2I+CqwJCIaM7OtfpVJW9ZFkOSzWbsFn8/qzarCpB8AQ/G5rN7pu0A78KPMXI/PZPVCEXEUcD+wDngf8Pf4TN6lOFJUvdUG4I2atteBd9ShFqm7rKZ4Lr+7znVI28tns3ZXq/H5rN5jY5iEz2X1QhFxCnAO8LlKIFprNT6T1Tv8CTiZYqTzj/GZvMsxFFVv9TLwzpq2gRT/AyP1ChHx/YgYV9V0LPAW8HydSpJ2lM9m7RZ8Pqu36iRM8rmsXiUihlKMCp2cmQsrbT6T1StlYT7FYkpj8Jm8y3H6vHqrR4GzO3YiohnoR/GQkXqLJ4HvRcR/UDyPrwRmV71jRuptfDZrd/EkPp/Vy3QWJuFzWb1IROwF3AH8Erg9IgZUDj2Fz2T1IhFxEvDxzPxGpWlD5ddF+EzepThSVL3Vg0BTRHyhsn8x8NvMfLOONUnbJDN/CtwC3A7MBn4DnFfPmqQd5LNZuwWfz+ptOguTKoHSQ/hcVu9xGvB+4EvAmqrtAXwmq3dZBEyKiIkRMRi4nOK+vROfybuUyMx61yBtl4gYC9xE8QflHsDfZOaf61qUJJVMRCRwcGYuq+yPxWezJO1UlWfvbZ0cOhg4Gp/LkrRTRcRpFAveHQTMBb6cmS/5d+Vdi6GoerWIOBD4IPBwZr5U73okST6bJWlX43NZknYdPpN3HYaikiRJkiRJkkrFd4pKkiRJkiRJKhVDUUmSJEmSJEmlYigqSZIkSZIkqVQMRSVJkiRJkiSViqGoJEmS1MMiok9E9Ktpa4yIbfr7eOUz79rKvkdExCe25fydnOPDEbHPjpxDkiRpV2QoKkmSJPW804E/RcRfVbXNBG6KiOaIGFvdOSKOjIi/rdr+W+XQOGD2Vn7nP1S+d4uicEhEfCEi7o2IEyqHfgqM3srvkyRJ6jUa6l2AJEmSVAIXAtMz89Wqtpco/j6+Hrg6IpZk5p8qxz4HHA48BhwN/AV4ApgEDIqIBRQDHPYCjs/M/6z+soj4JPBx4PmIWFxTy+vAKZn5YqXvx4DbgP8N9KMIU1dFxGDgncCtO3rxkiRJuxpHikqSJEk9KCLOACIzZ0fEDyLiw5VD64EAXgTOBD5aNSJ0A3BHZl4G/BJYHxGjgSHA+zLzcOAq4MFOAtH3Af8CnJCZ78nMYZk5DBgOrAGu7whEKx4A9qcIXBdn5qzMfBo4DdgDeC4iVla2NyPii935+yNJklQPhqKSJElSD4mIQ4Arga9GxH8H/g74q4iYBJwMTAAWAedTBJ4dav+e3gT8E3AXMCMi9gK+Dny35vs+CNwLfAc4LyK+VnX4e8CrwBU15+6YPRaVc+wREQ3A54HPZeagzBwEvIcirP31tvweSJIk7YqcPi9JkiT1nBOAA4FbgGZgIrBf5eengOczcxxARPQFjql8bhVFkPp9YDnFuz0/Bfypcq6HgJsy85ma7xsN/Dgzr4mIPwO/jIh3AyuB8cBxmflWzWe+STFK9ACKYLQNuBsYAdwZEeOBY4EbgfmZuWIHf08kSZLqLjKz3jVIkiRJu6VK0NlAEXZ+JzNPqbS/A5gM/N8Uoz+PrvR5jiK43FDpNw/4fGYuruwfAfy/wL4Uoz7/Hng4u/hLfWU6/h+B/wROzcyFXfTrRxHEzgNOpQhHB2fmsoiYAHwoM8/esd8NSZKkXYcjRSVJkqQekpnrI2IgMAv4NEBEfBW4GFgADKVYQOkGYJ/M/F2lz9XAHZXTfDEiWoDzKN4JOjUzH4yI4yimzw+NiA9kZmv1d1feQfoPFEHnmVsY4Xk68DLFqNbfAScC4yNiPpCV8/1N5Zoe2O7fEEmSpF2E7xSVJEmSekhE9AceB/YGflAZ+XlLZh6UmaMogsgHgC8CN0XE0MpH+1edZjWwEPg+8F7gpxGxDPgFxTs+P9gRiEbEgRHx9crq9HOAvwIGA3+IiGWV7eWIuLmm1IuA2cCKyvY3lbZXq/rsD8yujHKVJEnq1QxFJUmSpB6Sma9TLLR0IXAZ8LeZ+R9VXX5NsTDSaRTT5pd0cppbM/Mx4GmgJTObM7MZ+CwwIDNXA0TECcBjFKvM/x74ZUff6g2YBqztOHlE/F3lx/sqv36OIgB9vnpUaGbeDPxvikWhJEmSejVDUUmSJKmHVFZxv5XifZ0fAi6PiEsqx/YDDgbeB5ydmcsjornmFH2Az0XE3RRT7WttXDQpMx/OzHdn5kSKcHRzqt9BOpji/abVLgWu7uRz3wHGRURs4fySJEm7NN8pKkmSJPWcQylWjH8c+A3wE2B+ZfGi71G8S/Q+4F8i4v8C7o6IHwDHAWOAPwOvU4w03Qs4vjI1nsp+V+8JDWBMRCzu5NjewJ0dO5k5DSAiTqrsZ0ScAzwZEY0Uq9JvqBy7KyLu62phJ0mSpN7CUFSSJEnqIZnZEhH7ZWZbR1tlEaUTgb/LzHsrbY0UCy79EbiNYkGlWzPzP6s+dwIwLzP/j8r+8cAPu/jqvYDbM/PztQci4iKK0LVWI9CvUvfvK33/rdJ348rzlVcCSJIk9Wrhf/JKkiRJO09E7AWsz8wNNe3vBZZn5mtdfG4PoO/WhJIR0Rfok5lv7GCt/Q1BJUnS7shQVJIkSZIkSVKpuNCSJEmSJEmSpFIxFJUkSZIkSZJUKoaikiRJkiRJkkrFUFSSJEmSJElSqRiKSpIkSZIkSSoVQ1FJkiRJkiRJpWIoKkmSJEmSJKlUDEUlSZIkSZIklcr/D5hmN817uZuiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_广州=df.query(\"城市名称=='广州'\")\n",
    "df_广州_11=df_广州[\"路线名称\"].value_counts()\n",
    "name = df_广州_11.index\n",
    "collnum = df_广州_11.values\n",
    "plt.figure(figsize=(15,8),dpi=100)\n",
    "b = plt.barh(name,collnum,color='purple')\n",
    "for rect in b:\n",
    "    w = rect.get_width()\n",
    "    plt.text(w,rect.get_y()+rect.get_height()/2,'%d'%int(w),ha=\"left\",va=\"center\")\n",
    "plt.title(\"广州地铁线路站点数量\",fontsize=28)\n",
    "plt.ylabel(\"站点数量\")\n",
    "plt.xlabel(\"线路名称\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6220052",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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